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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES MEDICAL ACADEMY
Egl! Machtejevien!
PEPTIDE PATTERN OF AMNIOTIC
FLUID AND ITS CORRELATION
WITH PROTEIN COMPOSITION
OF FETAL MEMBRANES:
THE SEARCH FOR NEW POTENTIAL
BIOMARKERS TO PREDICT
PRETERM PREMATURE RUPTURE
OF MEMBRANES
Doctoral dissertation Biomedical Sciences,
Medicine (06B)
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This doctoral dissertation was carried out at the Lithuanian University of Health Sciences in 2008–2012.
Scientific Supervisor
!"#$%& '"%& ()*+& ,#-+.*+& /+012+34516.7& 891*:3+.1+.& ;.1<6"41*=& #$& >6+-*:& Sciences, Biomedical Sciences, Medicine – 06B)
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TABLE OF CONTENTS
ABBREVIATIONS ... 5
1. INTRODUCTION ... 7
2. AIM AND TASKS OF THE STUDY ... 9
2.1. Aim of the study ... 9
2.2. Tasks of the study ... 9
3. NOVELTY OF THE RESEARCH ... 9
4. REVIEW OF THE LITERATURE ... 10
4.1. “Omics” technologies ... 10
4.1.1. Human genome ... 10
4.1.2. Transcriptome ... 11
4.1.3. Proteome ... 12
4.2. Fetal membranes ... 20
4.2.1. The amniochorionic extracellular matrix proteins ... 20
4.2.2. Matrix metalloproteinases ... 21
4.2.3. Tissue inhibitors of metalloproteinases ... 22
4.3. Physiology of amniotic fluid ... 22
4.3.1. Composition of amniotic fluid ... 22
4.3.2. Regulation of amniotic fluid volume ... 23
4.4. Amniotic fluid proteome ... 24
4.4.1. The normal human amniotic fluid proteome ... 24
4.4.2. Gestational age-dependent changes ... 26
4.4.3. Clinical applications of amniotic fluid proteomics ... 28
4.5. Human plasma proteome ... 33
4.6. Methods of proteomic analysis of amniotic fluid ... 34
4.6.1. Gel electrophoresis ... 35
4.6.2. Protein arrays ... 35
4.6.3. Liquid chromatography ... 37
4.7. Preterm premature rupture of the membranes ... 46
4.7.1. Definitions and incidence ... 46
4.7.2. Risk factors ... 47
4.7.3. Etiology and pathophysiology ... 50
4.7.4. Diagnosis ... 53
4.7.5. Prediction of preterm premature rupture of membranes ... 56
5. PATIENTS, BIOLOGICAL SAMPLES AND METHODOLOGY ... 58
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5.2. Biological samples ... 60
5.3. The analytical system ... 62
5.4. Database searching and confidence of proteins identification ... 65
5.5. Ethical aspects ... 66
6. RESULTS AND DISCUSSION ... 67
6.1. Peptides and proteins identified in amniotic fluid ... 70
6.2. Characterization of amniotic fluid proteome ... 80
6.3. Comparison of the amniotic fluid proteome with previous publications ... 82
6.4. Gestational age-dependent changes in the amniotic fluid proteome ... 84
6.5. Fetal membranes proteome ... 88
6.5.1. Comparison of proteome from fetal membranes of patients with PPROM and term labor with intact membranes ... 89
6.5.2. Comparison of proteome from the fetal membranes and amniotic fluid of patients with PPROM and term labor with intact membranes ... 97
6.6. Comparison of biological samples peptidome and proteome from patients with preterm premature rupture of membranes ... 98
7. CONCLUSIONS ... 101
8. BENEFITS OF THE RESEARCH AND POTENTIAL FOR THE FUTURE ... 102
9. LIST OF ORIGINAL PUBLICATIONS ... 104
10. REFERENCES ... 106
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ABBREVIATIONS
2DE two dimensional electrophoresis2D LC/MS two dimensional liquid chromatography mass spectrometry 2D PAGE two dimensional polyacrylamide gel electrophoresis
AC amniocentesis
AF amniotic fluid
AFI amniotic fluid index AFP alpha-fetoprotein CVF cervico-vaginal fluid
Da dalton (the unified atomic mass unit) DNA deoxyribonucleic acid
ECM extracellular matrix
ELISA enzyme-linked immuno sorbent assay ESI electrospray ionization
fFN fetal fibronectin
FN false negative
FP false positive
G group group of amniotic fluid samples from patients at 16–18 week of gestation with intact membranes (obtained during prenatal genetic amniocentesis)
HLUHS Hospital of the Lithuanian University of Health Sciences HPLC high performance liquid chromatography
HPPP Human Plasma Proteome Project HUPO Human Proteome Organization
IAI intraamniotic infection
IEC ion exchange chromatography IUI intrauterine infection
Ig immunogloblin
IGFBP-1 insulin-like growth factor-binding protein 1
IL interleukins
LC liquid chromatography
MALDI-TOF matrix assisted laser desorption/ionization time-of-flight MD multidimensional
MDG Millennium development goal MMP matrix metalloproteinases
MR mass restricted
MS mass spectrometry
6 PCR polymerase chain reaction
pI isoelectric point (the pH at which a protein carries no net electrical charge or net charge is zero)
ppm parts per million
PPROM preterm premature rupture of membranes PROM premature rupture of membranes
PTD preterm delivery PTL preterm labor
Q-TOF quadrupole time-of-flight
R group group of amniotic fluid samples from patients with preterm premature rupture of membranes
RAM restricted access material RNR ribonucleic acid
RP reverse phase
SD standard deviation
SELDI-TOF surface-enhanced laser desorption/ionization time-of-flight SCX strong cation exchange
SPE solid phase extraction
TIMP tissue inhibitor of metalloproteinase
Z group group of amniotic fluid samples from patients with term pregnancies and intact membranes (obtained during cesarean section)
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1. INTRODUCTION
The Millennium Development Goals (MDGs) were set in 2000 by the United Nations. MDG-4 targets a two-thirds reduction of under 5 years children deaths between 1990 and 2015 [1]. While under age of 5 mortality rates are improving in many countries worldwide, neonatal mortality rates (deaths in the first 28 days of life) have shown much less progress. Neonatal deaths now account for more than 42% of under-5 deaths [2,3]. Com-plications of preterm birth are the leading direct cause of neonatal mortality, accounting for an estimated 27% of the almost four million neonatal deaths every year, and act as a risk factor for many neonatal deaths due to multiple causes, particularly infections [3]. Therefore, achievement of MDG-4 is strongly influenced by progress in reducing neonatal deaths. Since preterm birth is the leading cause of these deaths, therefore progress is dependent on achieving of evidence-based interventions to prevent preterm delivery; also to improve survival for preterm newborns.
Preterm premature rupture of membranes (abbreviated as PPROM) is defined as the rupture of fetal membranes before the onset of labor before 37 weeks of gestation. PPROM occurs in 2% to 5% of pregnancies and is the most common cause of preterm birth, present in 25% to 40% of cases, and can result in significant neonatal morbidity and mortality [4,5,6]. According to the Lithuanian Medical Data of Births 1616 (5.6%) newborns were born prematurely in Lithuania in 2011 [7].
Epidemiological and clinical studies have identified a number of factors associated with increased risk for PPROM; however, the current methods of predicting women are non-specific to be of real clinical value. It is likely that biological markers exists that could be of clinical value as the evident increase that many of the events leading to PPROM are more likely to be chronic than acute. Therefore, there is a need to develop and to apply highly advanced methodologies to search and identify these biomarkers. Once the biomarkers are confirmed, efficient and selective biological tests could be developed which would help to achieve accurate prognosis, diagnosis and maybe medicine to prevent that process.
The etiology of PPROM is thought to be multifactorial and the actual mechanisms involved are still unknown. Intrauterine infections caused by bacteria are considered to be a predominant cause/risk factor. It has been estimated that about 40% of all PPROM occur in mothers with intrauterine infection. Once the pathogen reaches the uterine cavity through an ascending route, the fetal membrane is the last barrier for pathogens to break
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before accessing the amniotic cavity. In this pathological scenario, the rupture of the amniochorion results from a degrading process that is potentiated by an exacerbated immunological response. Several scientific groups are working in order to understand the mechanisms related to infection and PPROM and have been focused on infection in the amniotic fluid. They have already identified a number of biomarkers specific to infection. The prognosis in PPROM is linked to maternal inflammatory markers that might predict perinatal infection, and therefore might be helpful to decide the timing of the delivery. However, the etiology of other 60% of PPROM cases, when the reason in not bacterial, remains unclear. Those cases are of the eminent interest.
Proteomic analysis, which combines two-dimensional liquid chroma-tography (2D LC) and mass spectrometry (MS), has found wide applications in protein screening in tissues obtained from healthy and diseased states for the discovery of novel diagnostic markers. The application of this new technology seems to have an important impact on the recognition of PPROM mechanisms. Improved understanding of these mechanisms should allow clinicians to design appropriate interventions so that the incidence of preterm birth and related fetal and neonatal morbidity and mortality will be significantly reduced.
Most of the time, the diagnosis of PPROM is done during physical examination. However, in 10–20% of equivocal cases, biological markers are needed to confirm the diagnosis, especially when the leakage of fluid is low or intermittent. In these cases, a quick and reliable diagnosis is neces-sary for applying the appropriate measures to reduce perinatal compli-cations.
In conclusion, detailed research is needed to identify potential bio-markers those could be used to predict patients at risk for PPROM and diagnose equivocal cases of PPROM.
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2. AIM AND TASKS OF THE STUDY
2.1. Aim of the studyThe aim of the study was to analyze the peptide composition of amniotic fluid and fetal membranes and link it to corresponding proteins in order to reveal the finding of new potential biomarkers of preterm premature rupture of membranes.
2.2. Tasks of the study
1. To investigate the peptide composition of amniotic fluid and link it to corresponding proteins.
2. To compare peptidomes of amniotic fluid depending on the gestational age.
3. To analyze proteomes of the digested fetal membranes and differentiate between preterm premature rupture of membranes and term pregnancies with intact membranes.
4. To analyze the peptidome and proteome of amniotic fluid from patients with preterm premature rupture of membranes and to search for new potential biomarkers for preterm premature rupture of membranes.
5. To compare peptidomes and proteomes of amniotic fluid, fetal membranes and maternal plasma from patients with preterm premature rupture of membranes.
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3. NOVELTY OF THE RESEARCH
This multidiscipline peptidome and proteome research incorporates obstetrics, biochemistry, analytical chemistry and highly advanced sepa-ration technology. For the first time in a single study peptidome and pro-teome of fetal membranes is directly compared to amniotic fluid propro-teome in PPROM and term pregnancies with intact membranes. Gestational age-dependent changes in peptidome of amniotic fluid during the second, early and late third trimesters of pregnancy are compared. The obtained dif-ferential peptide displays revealed new potential biomarkers of PPROM.
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4. REVIEW OF THE LITERATURE
4.1. “Omics” technologies4.1.1. Human genome
In 1944 deoxyribonucleic acid (DNA) as a molecule was discovered by Avery and coworkers, the determination of its structure to be a double helix was resolved by Watson and Crick in 1953 [8,9]. The exploration of the mechanisms of expression of genetic information has opened new op-portunities for further studies of human diseases and high technologies.
In humans, each cell normally contains 23 pairs of chromosomes, for a total of 46. The DNA in each chromosome constitutes many genes. A gene is a segment of DNA containing the code used to synthesize a protein. An organism’s complete set of DNA, including all of the genes, makes up the genome. According to recent estimates, the human genome appears is made up of approximately 25,000 genes. The genome includes both the genes and the non-coding sequences of the DNA [10]. Each genome contains all of the information needed to build and maintain the organism. The gene encodes instructions that allow a cell to produce a specific protein. Proteins control the phenotype of the cell by determining its structure and by carrying out all required functions in the cell. An accurate catalog of the protein-coding genes encoded in the human genome is fundamental to the study of human biology and medicine.
For a long time, complete characterization of the genome of various species has been an aim of the scientific community. The first genome to be sequenced was that of Haemophilus influenzae in 1995. Since then, several other genomes have been entirely sequenced. Begun formally in 1990, the Human Genome Project was a 13-year effort to identify all the genes in human DNA which has been completed in 2003 [11]. Landmark papers detailing sequence and analysis of the human genome were published in February 2001 and April 2003 issues of Nature and Science [12–13]. The three most widely used human gene catalogs (Ensembl, RefSeq, and Vega) *#?6*:6"&@#.*+1.&+&*#*+-&#$&A 24, 500 protein-coding genes [14–15].
The genome of an individual determines its potential for protein expression. However, it does not specify which proteins are expressed in the cells. The complete genome of an organism gives only a relatively static overview of the functional potential of an organism and does not describe the immense dynamic process which occurs in a living organism. For
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example, every somatic cell of butterfly and its caterpillar contains identical genetic information [16]. The conversion of this genetic information that is, the expression of the different genes into proteins takes place, however, during the different development stages of an organism as well as in dif-ferent cell types and under difdif-ferent environmental conditions. The absence of gene eliminates the possibility to synthesize certain protein what might directly lead to a disease; however the presence of the gene by itself does not guarantee the synthesis of the corresponding protein. This leads to an enormous individual phenotypic diversity.
Structural aberrations of the genome such as changes in the chro-mosome number and structure, changes in gene copy number, and mutations play a causal role in a number of diseases. Structural changes often result in functional genomics abnormalities, namely, changes in the gene expression patterns of individual cells. Genome-wide profiling of diseased tissues for gene copy number abnormalities has already been proven to be a fruitful strategy in cancer investigation. It is thought, that the information on the entire body of deregulated genes can be used to identify causal events in the disease and lead to the development of the personalized medicine. Therefore only the identification of coding sequences is insufficient to solve the future of personalized medicine and diagnosis.
Genomics is the study of genes or gene products in an organism. ! Structural genomics is the production and study of three-dimensional
structures of proteins. The structure of a protein is very important in determining its function.
! Functional genomics is the study of dynamic cellular processes such as gene transcription, translation, and gene product interactions that define an organism.
4.1.2. Transcriptome
After the age of groundbreaking scientific advances that took place in the middle of the twenties century, the past decades were devoted to clarification of the genotype – phenotype relationship. The basic mechanism how the genetic information contained in DNA is translated into proteins was deeply investigated. When a gene is expressed in a cell, the DNA sequence is copied by specialized enzymes – RNA polymerases – into RNA molecules during transcription. RNA molecules are processed through splicing into a messenger RNA (mRNA) which is then translated into a protein (Fig. 4.1.2.1).
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Fig. 4.1.2.1. Illustration of DNA, mRNA, proteins and metabolites
processing within the cell
Profiling of the mRNAs expressed by the genome is called transcript-tomics [17]. This gives us an idea of the genome’s plans for possible and probable protein synthesis at that moment. Transcriptomics has the advantage over proteomics that the technology is simpler. Transcriptomics can therefore give important biological information about what genes are turned on (expressed) or turned off (repressed), and when. A major disad-vantage is that, although the snapshot provides the genome’s plans for protein synthesis, it does not represent the realization of those plans. The correlation between mRNA and protein levels is poor because many pro-teins are modified after they have been translated, so that one mRNA can give rise to more than one protein. Furthermore, the location and concen-tration of synthesized protein as well as post-translational complexation with other proteins might play an enormous role to the protein activity and function.
4.1.3. Proteome
After the Human Genome Project was finished, an increasing demand for a functional analysis of gene products in order to understand the physiology has made proteomics, peptidomics and metabolomics highly valuable and promising technologies. The state of the organism is reflected to the key process in the living body – protein metabolism. One of the greatest challenges facing researchers in the post-genomic era is to identify, quantify and localize all expressed proteins and peptides. Proteomics is one of the most important approaches to understand gene function, because proteins expressed by genes are ultimately responsible for our phenotype. Proteins are synthesized by the translation of mRNA into polypeptides on ribosomes. Proteins are found in different cell compartments (cytoplasm, a
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range of intracellular organelles) or as secreted extracellular proteins in various body fluids.
The term proteome originates from the words PROTEins expressed by the genOME and it was first used by Marc Wilkins at the first proteomic conference in 1994 [18,19]. It describes the expressed protein complement of a cell or a tissue at a given time. Proteomics is the large-scale study of gene expression at the protein level, which will ultimately provide direct measurement of protein expression levels and insight into the activity state of all relevant proteins [20]. The goal of proteomic research is the com-prehensive, qualitative, and quantitative analysis of all proteins expressed by genes as well as the description of changes occurring at the protein level under the influence of biological stimuli such as diseases or drug treatment. The aim of clinical proteomics is to find the function of every protein.
The proteome, unlike the genome, is not a fixed status in the organism and it changes. One gene leads to many gene products – proteins, peptides and they became different depending on site and time. Thus, every organism has one genome, but many time dependant proteomes.
The analysis of the proteome is by far much more complicated than in genomics. While the human genome sequencing endeavour was dealing with a static system composed of only four building blocks, the following battle of conquering the human proteome was of significantly higher com-plexity, namely dealing with a dynamically changing system of 20 amino acids (in humans) with a substantial range of post-translational modifica-tions (which are about 100 variamodifica-tions) and huge concentration differences. The dynamic range of protein expression, which stretched over the several orders of magnitude (zeptomole or yactomole per liter) with highly abun-dant proteins such as albumin in plasma or very low protein concentrations, makes the identification of the entire proteome a far more difficult and more complex challenge than the sequencing of the genome. An additional chal-lenge rises from the fact that in proteomics so far we do not have an am-plification technique, similar to polymerase chain reaction (PCR) technique which enables to create a desired number of DNA chains from a single copy. Therefore, proteins at lower concentrations detected with a higher error ratio, low protein concentrations cannot be detected at all. In con-clusion, proteomics bears a much higher degree of complexity than geno-mics, a fact which was totally underestimated when starting proteomics. Any protein, though a product of a single gene, may exist in multiple forms that vary within a particular cell or between different cells. In addition, most proteins exist in several modified forms because of different
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lational modifications such as phosphorylation or glycosylation. These and other post-translational modifications are crucial for the protein function, because they affect protein structure, localization and function [21].
In summary of most characteristic features in the field of proteomics are:
1) chemical constituents of widely different structure (peptides, proteins, and different modifications: sugars, carbohydrates, nucleosides, etc.), 2) extremely large number of constituents (> 1 million),
3) high diversity in the abundance ratio (1:109),
4) large range of molecular weight (from 100 to several million Da), 5) constituents with relatively small differences in chemical structure for
example post-translational modifications of proteins: glycosylated, phosphorylated etc.; chemically small differences, however biologi-cally highly relevant,
6) number of detected constituents increase exponentially with decreas-ing concentration i.e. increasdecreas-ing the sensitivity.
The Human Proteome Project was launched in September 2010 with the goal of characterizing at least one protein product from each protein-coding gene [22]. In 2013 Farrah et al. assessed how much of the proteome has been detected to date via tandem mass spectrometry by analyzing PeptideAtlas, a compendium of human derived LC/MS/MS proteomics data from many laboratories around the world. It was found that this latest PeptideAtlas includes at least one peptide for each of !12500 Swiss-Prot entries, leaving !7500 gene products yet to be confidently cataloged.
4.1.3.1. Peptidome
Proteomics is a highly valuable technology for a functional analysis of gene products in oder to understand the physiology, but is restricted to proteins that are larger than 10 kDa [23]. The subproject of proteomics, namely the study of all peptides expressed by a certain cell, organ or orga-nism, is termed peptidomics. The term peptidomics was introduced in 2001 [24]. In analogy with proteomics, the aim of peptidomics is to identify all peptides. Peptides and small proteins like hormones, cytokines or growth factors act like messengers and play an essential role in the living systems with the high impact on human health. Peptidomics comprises not only peptides, originally synthesized by an organism to perform a certain task, but also degradation products of proteins (degradome). Peptidome is
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mechanistically linked to the proteome as the cycle of protein maturation, activation, and degradation as well as the distribution between is regulated by proteases and counter-regulated by protease inhibitors. Therefore, pro-teolytic cleavage of proteins leads to peptides as indicators of protease activity and degradation. Degradome is a very important part of the protein metabolism, and thus also reflects the organism state. Peptidomics through differential peptide displays, peptide composition and amino acid sequence information delivers one insights into biological processes. However, pep-tidomics is far more challenging compared with genomics and proteomics.
The proteome/peptidome analysis usually includes the following stra-tegies: native protein pre-separation, then digestion followed by separation and identification, or alternatively straight digestion, separation and identi-fication by mass spectrometry. Therefore, starting with one protein, after digestion will end up with approximately 30 to 70 short peptide fragments. Identification of only very few of them will provide sufficient information which protein was present in the sample. Peptidomics does not possess such feature: from the beginning of the analysis to the end we have only one peptide at a certain concentration and we have to identify it. However, when peptides come from the degradome of proteins, then, naturally, peptidomics is in similar situation as proteomics. Then bioinformatics and statistics allow the assignment of the peptide fragments to the original protein.
Several promising attempts have been made to analyze the peptidome by Richter et al. [25,26]. They constructed the human circulating peptide database between tissues. To establish a mass database, all 480 fractions of a peptide bank generated from human hemofiltrate were analyzed by matrix assisted laser ionization time of flight (MALDI-TOF) mass spectrometry. Using this method, over 20,000 molecular masses representing native, cir-culating peptides were detected. Estimation of repeatedly detected masses suggests that approximately 5,000 different peptides were recorded. More than 95% of the detected masses were smaller than 15,000, indicating that the human hemofiltrate predominantly contains peptides.
4.1.3.2. Biomarkers
The general definition of a biomarker is an indicator of a biological state [27]. In medicine it is used to evaluate and measure normal biological processes, the presence or progress of disease or the effects of therapeutic intervention [28]. Proteomic and peptidomic analysis offers a powerful approach to identify disease-associated proteins and peptides that can be used as biomarkers for diagnosis and as drug targets for treatment.
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Alterations in proteins abundance, structure, or function, act as useful indicators of pathological abnormalities prior to development of clinical symptoms and as such are often useful diagnostic and prognostic biomar-kers of a particular disease. In addition, proteins are the primary targets of most drugs and are the main basis for the development of new drugs. Also peptides hold great promise to be found as biomarkers.
Differential analysis between diseased and healthy material, treated and control is a powerful approach to detect statistically significant changes in protein expression levels. In practice it is very rare that a protein is either present or completely absent. In most cases only partly up- and down-regulations of certain proteins are observed. These quantitative changes should be determined with precision and confidence, but it is a very la-borious task.
In a biomarker discovery the main task is to find and identify novel, disease associated proteins and peptides through the systematic differential protein displays. The value of such biomarkers is based on their combi-nation of high specificity and selectivity for the biological process in which it takes place. The functions of the detected biomarkers must be proven by a second entirely independent analysis method. In most cases Western Blotting is employed for this task [29]. Identifying disease markers, proteins or peptides that appear or disappear during the course of a disease, do not necessarily require that all expressed proteins/peptides in a clinical sample should be identified – although the more complete the proteome, the more complete will be any set of markers. Therefore, there is a mutual need of highly efficient techniques to perform human proteomic/peptidomic maping to accelerate findings of biomarkers providing an answer about the health state of the patients.
Because of possible diseased location heterogeneity and other biases that might be related with biomarker identification and evaluation processes, it is essential that the identification of biomarkers should proceed in a systematic manner. In 2002, the National Cancer Institute’s ‘Early Detection Research Network’ developed a five-phase approach to systematic disco-very and evaluation of biomarkers which could be used in other fields of medicine as well. In general, biomarker development should follow an orderly process wherein one proceeds to the next phase only after meeting pre-specified criteria for the current phase [30]. In the phase 1 the focus is set on studies of preclinical exploration. Biomarkers are discovered through knowledge accumulation on gene expression profiling or protein profiling to distinguish diseased and normal samples. Identified markers are prioritized
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based on their diagnostic/prognostic/therapeutic (predictive) value that could suggest their evolution into routine clinical use. Upon successful com-pletion of phase 1 requirements, an assay is established with a clear intended clinical use. The clinical assay could be a protein, peptide, RNA or DNA based technique, including enzyme-linked immuno sorbent assay (ELISA), protein profiles from MS, phenotypic expression profiles, gene arrays, antibody arrays or quantitative PCR. In order to ensure documented clinical usefulness, such techniques firstly need to be validated for reproducibility and also proven to be transferable among different laboratories. Then, the assays should be evaluated for their clinical performance in terms of ‘sensitivity’ and ‘specificity’ within thresholds determined by the intended clinical use. In phase 3 an investigator evaluates the sensitivity and spe-cificity of the test for the detection of diseases that have yet to be detected clinically. Samples analyzed in this evaluation phase are taken from study patients before the onset of clinical symptoms, with active follow-up to ascertain disease occurrence. Usually this phase is very time-consuming and expensive to perform; therefore, phase 3 should consist of large number of intervention trials whenever possible. This is there biomarker will become ready for clinical use once validation studies will end. Phase 4 evaluates the sensitivity and specificity of the test. An investigator can estimate the false referral rate based on tested biomarkers and describe the extent and characteristics of the disease detected. These studies are difficult to perform specifically for rare diseases. Phase 5 seeks to evaluate the overall benefits and risks of the new diagnostic test on the screened population group. The cost per life saved is one example of an endpoint for such a study. Again most probably this will require a large-scale study over a long time period and could also be prohibitively expensive. At the end of 5 phases de-termined biomarker should meet the following criteria: it should be safe and easy to measure, the cost should be relatively low, and it should be con-sistent across genders and ethnic groups. Despite intensive global efforts, most recent biomarker publications, have largely reported the inability to validate the biomarker for clinical use, rather than successful validation [31]. In fact, no new major cancer biomarker has been approved for clinical use for at least 25 years, despite the availability of highly sophisticated and powerful technologies and major advances in other areas of biomedical science. Although there have been over 10,000 publications on biomarker discovery with proteomics, a single proteomics-based diagnostic test approved by the Food and Drug Administration was HE4 protein for ovarian cancer in 2009; it was approved for monitoring recurrence. It measures five
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different proteins in the blood, and is not used to screen for ovarian cancer, but to help evaluate whether an ovarian mass is benign or malignant prior to surgery [32].
Proteomics based identification of biomarkers for fetal abnormalities and pregnancy complications in amniotic fluid have made significant progress in the past five years. This is attributed mainly to advances in mass spectrometry-based proteomic technologies that enable new strategies for discovering biomarkers from complex biological fluids. These markers, although they still need to be verified, are diagnostic and may in the future provide targets for therapeutic intervention [33]. It is expected that peptides themselves can be used as biomarkers to monitor effectiveness and safety of drugs and to identify disease in very early stages.
4.1.3.3. Biological samples
Physiological and pathological changes are reflected in the production and the metabolism of proteins and peptides. Peptides, specifically derived by distinct proteolytic processing of specific tissue proteins, yield biomarker information. Readily released from tissue, they are detectable in extra-cellular body fluids, including blood plasma, amniotic fluid, cervicovaginal fluid, cerebrospinal fluid, synovial fluid, breast milk, urine, etc. [34]. The analysis of human body fluids constitutes one of the most important app-roaches to the diagnosis of disease and in following therapeutic inter-ventions. Human body fluids carry information about the status of the organism that may help in the recognition of physiological misbalances when overt pathological symptoms are not yet present. Analyzing the con-stituents of body fluids presents a number of challenges, the most difficult being the discrimination between variability in composition caused by an ongoing disease process and natural variability. This variability is most obvious when one is analyzing samples from different persons (cross-sec-tional studies) but is also present, albeit to a lesser extent, when one is ana-lyzing samples from the same person over a given time period (longitudinal studies) [35]. Variability cannot be avoided but may be reduced by careful selection of the study population. At any rate, the discovery of disease-related changes in the composition of body fluids requires the study of a significant number of samples from patients and controls and necessitates a careful statistical interpretation of the results.
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Protein samples of biological origin are by nature highly complex and require sophisticated analytical tools to provide reliable analysis of the components.
4.1.3.4. Ethical issues in proteomics and peptidomics
Over the last two decades, medical research has begun to make extensive use of products of human origin in all “omics” studies. The phy-sical risks involved in donating human samples for research are usually minimal, but the risk that information from laboratory tests on a sample might harm the donor or their interests must not be forgotten. Informed consent is required from the donor and the biological sample should be treated as a gift [36].
So far, the ethical and regulatory framework for using human tissue in biomedical research is still vague, and varies between different countries. Biobanks are facilities or institutions storing materials generated from the human body. Body substances (e.g. blood, amniotic fluid) and tissue (e.g. fetal membranes) but also genetic data can be stored in a biobank.
There are different factors influencing proteomic research using hu-man samples, which are related to the patient (the supplier), to the user (the researcher), and to ethical, legal and economic framework conditions. Ethics committees usually deliver authorization for sampling a few millilitres of blood or plasma in patients or in normal volunteers easily. In this respect, proteomics researchers might benefit from favorable framework conditions. However, the problem of plasma analysis in biomedical proteomics research is complicated by the large quantities of plasma that can be necessary for identifying certain peptides present in a very low concentration, so that the plasma of hundreds of patients has to been pooled. Proteomics often requires repeated analyses over the course of disease. Of course, anony-mization of probes is not directly compatible with such follow-up studies. The problem can be solved by contracting a third party for anonymization and follow-up tasks, so that the biological information never comes in to contact with the patient’s identity [37]. Finally, another important specificity of proteomics studies is that they do not amplify genetic information, so that the data protection and privacy issues are less important than when performing, for example, genome-wide cDNA expression studies. However, researchers should not overestimate this difference since even a single, but significant piece of information gained from the protein pattern might imply significant privacy issues.
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4.2. Fetal membranes
Although the significance of PROM has long been recognized, the nature of the process leading to a failure of fetal membranes is poorly understood. Rupture processes are intrinsically mechanical, but the mechanisms by which biological and mechanical factors are associated with PROM are mandfatory to be investigated.
Fetal membranes are composed of two layers: the amnion and the chorion [38]. The amnion is composed of five layers: the epithelium, basement membrane, compact layer, fibroblast layer, and the spongy layer. Amnion is the innermost structure facing amniotic cavity and is lined by amnion epithelial cells. Amnion cells are purely fetal in origin and is biologically active during pregnancy. The chorion is composed of a reticular layer, basement membrane, and trophoblast layer. Although thicker than amnion, the chorion plays only a minor role in maintaining the tensile strength of the fetal membranes [39]. The amniochorion is composed of cells and extracellular matrix (ECM).
4.2.1. The amniochorionic extracellular matrix proteins
The amniochorionic ECM proteins synthesized by several cell types within the amnion and chorion confer both strength and elasticity to fetal membranes [40]. The breakdown of these proteins is regulated by matrix metalloproteinases (MMPs) and their inhibitor ratio. The ECM is composed of an interlocking mesh of fibrous proteins and proteoglycans. ECM proteins:
1) Collagens. Interstitial collagens are located in the compact layer of amnion. Type I and III (and smaller amount of types V and VI) are the pri-mary regulators of tensile strength. The cellular source of interstitial colla-gens is unclear. Casey et al. found that both epithelial and mesenchymal cells produce interstitial collagens [41]. It seems as mesenchymal cells express significantly higher levels of collagens I and III than epithelial cells. The epithelial cell contribution is likely to be dependent upon gestational age, as the density of mesenchymal cells in the amnion decreases in the later pregnancy. Type IV and VII collagens also make important contributions to the integrity of the fetal membranes. Type IV collagen, a basement mem-brane protein, is produced of both epithelial cells of the amnion and chorion. It assists in adhesion of other components of the basement membrane, such as laminin or heparin sulfate proteoglycans [42]. Type VII is expressed by
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epithelial cells of amnion. It stabilizes the fetal membranes by creating anchoring fibrils that link the basal lamina of the amnion to the ECM components [43].
2) Elastins are synthesized by fibroblasts, in contrast to collagens, give elasticity to tissues, allowing them to stretch when needed and then return to their original state.
3) Laminins interact with collagen VII to stabilize fetal membranes as mentioned above.
4) Fibronectins are glycoproteins that connect cells with collagen fibers in the ECM. It can be thought to be "trophoblast glue" and is found at the placental-uterine and decidual-fetal membrane interfaces. It is releases when the ECM of chorionic-decidual interface is disrupted. It is used as a biochemical marker for diagnosis and prediction of preterm labor.
A balance between the synthesis and the degradation of membranes components is physiologic throughout the gestation. Two main mechanisms are involved in the degradation process: apoptosis in the cellular compartment and ECM degradation by MMPs [44]. Regulation of MMP is depending on factors increasing their expression (cytokines) and factors decreasing their activity tissue inhibitor of metalloproteinases (TIMPs). Particular conditions can induce an unbalance between synthesis and degradation leading to the weakening of membranes. Different factors can be associated to induce this unbalance: infection, hormonal factors, and default in membranes fusion, oxidative stress and mechanic factors. The spontaneous rupture of the membranes is always occurring in regard of the uterine cervix after a process started several weeks before.
4.2.2. Matrix metalloproteinases
Matrix metalloproteinases are a large family of calcium-dependent zinc-containing endopeptidases, which are responsible for the tissue remodeling and degradation of the extracellular matrix [45]. The human MMP family currently consists of 26 members and is classified according to substrate specificity into collagenases, gelatinases, stromelysines, matrily-sins, membrane type-MMPs and other MMPs. Aberrant ECM degradation by activation of the MMP cascade or an imbalance between MMPs and their tissue inhibitors have been implicated in the pathogenesis of preterm labor and rupture of membranes [46]. PROM is associated with increased levels of active, TIMP free forms of MMP 2 and 9, in the amniotic fluid.
Intra-23
amniotic infection was associated with a significant increase in amniotic fluid MMP-3 concentrations in both women with preterm labor and intact membranes, and women with preterm PROM [47]. The intrauterine infection (IUI) triggers MMP production via inflammatory mediators [48].
4.2.3. Tissue inhibitors of metalloproteinases
TIMPs are endogenous specific inhibitors that have been shown to regulate the proteolytic activity of MMPs in normal and pathological processes [49]. A family of protease inhibitors include: TIMP-1, TIMP-2, TIMP-3, and TIMP-4. A fully functional TIMP network has been demons-trated in human fetal membranes [50,51] in placenta and decidua, and in amniotic fluid during the second trimester [52]. The majority of studies focused on TIMP-1 and TIMP-2. TIMP-1 concentrations in AF were in-creased in the presence of IUI and in patients with rupture of the membranes either term or preterm. In contrast, TIMP-2 levels were decreased in women with IUI and rupture of membranes.
4.3. Physiology of amniotic fluid
Amniotic fluid is fundamental for the normal development of the fetus. It protects the fetus physically and biochemically. AF resides in the amniotic cavity that is lined by the fetal membranes.
4.3.1. Composition of amniotic fluid
Amniotic fluid is constituted of about 98–99% of water. The amniotic sac, which contains the embryo, forms about 12 days after conception. AF immediately begins to fill the sac [53]. During embryogenesis, AF is ini-tially formed from maternal plasma that passed through fetal membranes. Because free diffusion occurs bidirectionally between the AF and the fetus across fetal skin, placenta, and umbilical cord from 10 to 20 weeks of gestation, AF composition becomes similar to that of fetal plasma during this period. Therefore, analysis of AF composition before skin keratini-zation, which occurs between 19 and 20 weeks of gestation, would reveal valuable information that may indicate physiological or pathological con-ditions of the fetus. Fetal urine first enters the amniotic sac at 8–11 weeks’ gestation and makes up most of the AF throughout the second half of
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pregnancy. The biochemical composition of AF is complex and varies with the gestational age. AF contains proteins, amino acids, carbohydrates, hormones, lipids and electrolytes. In contrast to other biological fluids, like plasma and serum, AF has a low protein concentration and relatively high carbohydrate and lipid content. Many of the protein molecules present in AF are structurally glycoconjugates and are protected against proteolytic attack from the extracellular matrix proteases. The increasing levels of enzymes and electrolytes in the later part of gestation correlate with the formation of the fetal kidneys, lungs, and the gastrointestinal tract. Studies have revealed the occurrence of growth factors, innate immunity molecules, and serum components in AF that are believed to be involved in growth, development, and protection of the fetus from infection [54]. The concentration of each protein in the AF is governed not only by fetal, placental, or maternal synthesis and degradation, but also by exchanges between the mother and the fetus through the placenta. Fetomaternal transfer of proteins involves several different mechanisms. Consequently, the concentration of each AF protein results from a balance between opposing dynamic metabolic and physiological processes, which proceed simultaneously.
4.3.2. Regulation of amniotic fluid volume
The amniotic fluid volume is related to the gestational age. The quan-tity of AF is the balance of water exchange between the mother and fetus, and is maintained within a relatively narrow range during all stages of pregnancy [55]. The amount of AF is highly regulated, although the exact mechanisms for regulation are not entirely clear [56]. Initially AF produc-tion is attributed to the amniotic epithelium and later to fetal kidneys and lungs [57]. Therefore, the two main sources of amniotic fluid are fetal urine and lung fluid, with an additional small contribute due to secretions from the fetal oral-nasal-tracheal cavities. The capillary bed in the fetal skin is also utilizes as an exchange surface. Part of AF may be derived from water trans-port across the highly permeable skin of the fetus, at least until kerati-nization of the skin occurs (intramembranous pathway). Transfer through the umbilical vessels is also believed to play a role in AF production. The two primary routes of amniotic fluid removal are fetal swallowing and absorption into fetal blood perfusing the fetal surface of the placenta and membranes (transmembranous pathway). Approximately half of the daily fetal urine output is eliminated by fetal swallowing.
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4.4. Amniotic fluid proteome
Proteomics allows simultaneous study of a multitude of proteins and is of great importance to gain insight into the physiology of amniotic fluid. A proteome is never static; therefore a snapshot of a protein expression status without any biological context cannot contain valuable information. However, proteome maps are necessary for establishing databases for protein identification and characterization. Amniotic fluid contains large amount of proteins and peptides produced by the fetal membranes cells, fetal tissues, fetal excretions and placental tissues [58]. The amniotic fluid proteome is therefore composed of urine proteins, intestinal proteins, alveolar fluid proteins, and their degradation products. In addition, cellular proteins are produced, either by the skin of the fetus or directly by the amnion. Amniocentesis is a method used to obtain samples for amniotic fluid proteome analysis. In order to identify patterns within the complex proteomic profile that can discriminate between normal and disease states it is needed to know the normal amniotic fluid proteome. A systematic analysis of proteins present both in AF and maternal serum could lead to the development of new noninvasive diagnostic procedures.
4.4.1. The normal human amniotic fluid proteome
Amniotic fluid is a potential source of biomarkers for many disorders that may occur during pregnancy or for embryonic abnormalities. The first detailed study of the amniotic fluid proteome was published in 1997 by Liberatori et al. [59]. The authors identified 31 human AF protein in AF supernatant by two dimensional electrophoresis followed by postseparation analysis techniques such as N-terminal sequencing of human AF obtained at the 17th week of gestation. At this time AF is most commonly obtained for prenatal diagnosis of chromosomal abnormalities by amniocentesis.
In 2004 Nilsson et al. identified 43 proteins in AF proteome [60]. The AF sample (n = 1) was taken at the 15th week of gestation from a healthy 36 year old woman. AF sample was digested and peptides were separated by gradient capillary LC followed by electrospray ionization and mass spectrometric detection with a 9.4T Fourier transform ion cyclotron reso-nance mass spectrometer. They were the first to use MS for profiling AF. They were also the first to deplete albumin from AF in order to identify more proteins. In addition, the study revealed that a combination of different
26
proteomic methods should be used to evaluate the proteome of amniotic fluid globally.
In 2006, three groups analyzed normal AF proteome. Park et al. reported 37 proteins (n = 8, term pregnancy) by using 2DE followed by MALDI-TOF-MS [61]. Michel et al. identified 69 proteins (n = 10, term pregnancy) from albumin-depleted AF by Off-Gel electrophoresis LC/MS/MS [62]. Tsangaris et al. identified 136 proteins (n = 16, 16–18 weeks of pregnancy) by 2DE followed by MALDI-MS/MS [63]. These different groups not only used different approaches as well as different protein databases, but also applied different levels of stringency for protein identification that makes difficult to assess the accuracy of each data set. As illustration, the group who identified the highest number of proteins also has identified many non-human proteins from human AF.
In 2007, Cho et al. reported on the most extensive protein profile of the second trimester normal human AF, which is comprised of 1026 unique gene products from 842 different genes [64]. AF samples (n = 16) between gestational ages of 16 and 18 weeks were taken from women carrying chromosomally normal fetuses. Three samples were fractionated by strong anion exchange LC, another three were fractionated by strong cation exchange LC, and 10 samples were pooled together and fractionated by LC 2D PAGE. The protein analysis followed by a common reverse phase LC/MS/MS. Mascot and The Global Proteome Machine engines were used to search the International Protein Index human database for peptide sequence identification. The list of proteins was generated by combining the results of both engines. All proteins that were previously reported were identified in this study. Assuming that all of the proteins identified in previous publications and in this study are correct, a total of 936 proteins have been identified from human AF so far. Despite interest regarding composition and functions of amniotic fluid, there have been limited attempts to generate an in-depth analysis of its proteome. Each identified protein was assigned a subcellular localization based on information from Swiss-Prot, Entrez Gene, and Gene Ontology databases. The cellular distribution of 558 identified proteins with known localization was reported. The majority were extracellular (42%) and membrane (26%) proteins. Tissue expression of each protein was searched from Swiss-Prot, Entrez Gene, and Gene Ontology databases. The tissue expression of 301 proteins was identified. Some of the organs to which many proteins were attributed include kidney, placenta, lung, liver, and heart. 24 proteins were specifically annotated as being expressed from embryonic organs/tissues. The authors
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utilized Ingenuity (Ingenuity Systems) to retrieve known functions of each protein. 221 (of 842) were matched with functions to retrieve known functions of each protein. Major categories included cellular movement, development and function of organs, cellular growth and proliferation, cancer, and cell-to-cell signaling. The top 15 proteins with the largest number of unique peptides with the top 15 proteins from the human plasma proteome were compared. Among these 15 abundant protein4&$"#B&CDE&F-$6*#G"#*61.E& *"+.4$#"B1.?& ?"#H*:& $+@*#"& I-induced protein ig-h3 precursor, and periostin are found at relatively low concentrations in plasma and are not included in the top 15 plasma proteins. Conversely haptoglobin, which is one of the most abundant proteins in plasma, was found at low concentration in AF, and apolipoprotein B was identified in AF by only one group, indicating its low abundance in AF.
The major challenge and the bottleneck in proteomics lie between protein discovery and target validation. Proteins with potential as bio-markers should be selected for further comparative analysis of expression and structural modifications with samples from normal and abnormal pregnancies. Currently used markers have insufficient individual detection rate and specificity; therefore the use of multiple markers is necessary.
4.4.2. Gestational age-dependent changes
Many proteins detected in AF are already present at a very early stage of gestation, whereas other proteins are detected only at the end of the pregnancy [65]. The protein composition and concentration of AF varies throughout pregnancy.
Michaels et al. analyzed AF samples from three trimesters of preg-nancy [66]. The authors used differential dye labeling of proteins resolved by 2D PAGE to determine the general differences in AF protein com-position over time. Totally 219 AF proteins were identified. The largest protein abundance changes appeared to be between the first and second trimesters. The changes seen in expression of the proteins are indicative of the role the molecules have in fetal development. Among the proteins that show increased level are Apo A1, Apo A2, IGFBPs, gamma glutamyl transferase 4, and pigment epithelial derived factor. The increase of apoli-poproteins between the first and second trimesters may contribute to the fetal lung development that occurs at this stage. The increase in the level of gamma glutamyl transferase 4 is showing increases in metabolic enzymes during pregnancy. The relative amounts of kininogen, ceruloplasmin,
angio-28
tensinogen, alpha 2 HS glycoprotein, orosomucoid, and ubiquitin are decreased between the first and second trimesters. The significance of this change is not clear, as the function of these molecules is not understood. It is likely that the immediate expression of these proteins is most important during early fetal development that occurs during the first trimester. The authors also identified a set of proteins consistently expressed in all three trimesters. Transthyretin and several IGFBPs were present at high levels throughout gestation. These proteins may have utility as controls for the normalization of differentially abundant biomarkers in diagnostic multi-analyte assays.
Queloz et al. compared the proteomic profiles of normal AF obtained at 17 and 40 weeks of pregnancy using 2DE and silver staining, as well as two-dimensional difference in gel electrophoresis [67]. Results showed that some proteins were more abundant in early pregnancy, while others were over expressed at term, suggesting that the protein profile of AF is dynamic and changes occur during development. These observations are particularly important when biomarkers for a specific condition are identified.
4.4.3. Clinical applications of amniotic fluid proteomics
Researches focus on the emergence of proteomics as a major platform technology in studying AF and developing biomarkers for fetal aneuploidies [68] and pregnancy related disorders. Pregnancy related disorders such as preterm premature rupture of membranes, preterm labor and intraamniotic infection (IAI), intrauterine growth restriction, preeclampsia [69] contribute significantly to maternal and fetal mortality. Although several pathways for the pathogenesis of pregnancy complications have been proposed, the basic molecular mechanisms that modulate these events remain incompletely understood. Discovery of clinically and biologically relevant biomarkers able to reveal key pathogenic pathways and predict pregnancies at risk for antenatal fetal damage is a priority. Proteomics provides a unique oppor-tunity to fill this gap [35].
4.4.3.1. Premature rupture of membranes
In 2003 Vuadens et al. identified new potential biomarkers for premature rupture of membranes [70]. This result was achieved by research group of !"#$%& ,%'%& J144#*& from Switzerland. Proteomic studies were per-formed on samples collected from women at term (pairs of maternal plasma
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and AF) as well as on samples of AF collected at the 17th week of gestation.
Their study was based on two-dimensional gel electrophoresis differential display between AF and plasma samples, followed by micro-sequencing analysis of specific spots. Two „amniotic fluid-specific“ proteins were identified. These peptides were fragments of proteins which are present only in AF but absent in normal human plasma of corresponding mother. These two peptides were identified as COOH-terminus fragments of agrin (appa-rent molecular weight: 19.1 kDa, pI: 5.3; SwissProt: O00468) and perlecan (apparent molecular weight: 19.6 kDa, pI: 5.62; SwissProt: Q9H3V5), respectively, both of which are heparan sulfate proteoglycans. These results were further confirmed by Thadikkaran et al. [71]. Their physiological roles in amniotic fluid remain unknown. However, they are thought to mediate the action of growth factors and be involved in developmental processes. The origin of these peptides and possible roles are reviewed by Cretazz et al. [67].
Michel et al. applied the Off-Gel isoelectric focusing technique followed by tryptic digestion of the proteins and by LC/MS/MS to analyze the plasma and AF sample from a woman at term pregnancy. Totally 73 and 69 proteins were identified in maternal plasma and AF samples. Proteins, found in AF have been compared to those identified in the mother plasma as well as to the reference human plasma protein list [72]. Systematic com-parison revealed that nineteen proteins were specifically present in the AF and absent in maternal plasma and may be considered as potential markers of PROM (Table 4.4.3.1.1). Among these proteins, amiloride-sensitive amine oxidase [73,74] and perlecan have already been recognized as potential biomarkers of PROM by other researchers previously [72].
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Table 4.4.3.1.1. List of the proteins identified in AF and absent in maternal
plasma Swiss-Prot
accession number
Protein name
O75363 Breast carcinoma amplified sequence 1 O94832 Myosin Id
P07093 Glia derived nexin precursor P10451 Osteopontin precursor
P13535 Myosin heavy chain, skeletal muscle perinatal P13987 CD59 glycoprotein precursor
P19801 Amiloride-sensitive amine oxidase [coppercontaining] precursor (EC1.4.3.6) P35527 Keratin, type I cytoskeletal 9
P46100 Transcriptional regulator ATRX
P98160 Basement membrane-specific heparan sulphate proteoglycan core protein precursor (perlecan)
Q03519 Antigen peptide transporter 2 Q12841 Follistatin-related protein 1 precursor Q13421 Mesothelin precursor
Q14204 Dynein heavy chain, cytosolic Q14644 Ras GTPase-activating protein 3 Q8N3R9 MAGUK p55 subfamily member 5 KLM,KN& Protocadherin 16 precursor
Q9NTG1 Polycystic kidney disease and receptor for egg jelly related protein precursor Q9Y4C8 Probable RNA-binding protein KIAA0682
The role of these proteins in amniotic fluid is still unknown. Accord-ing to Michael et al., among the proteins identified as beAccord-ing specifically present in AF several are linked to pregnancy. Transcriptional regulator ATRX could be a global transcriptional regulator. It modifies gene expres-sion by affecting chromatin, and it may be involved in brain development and facial morphogenesis which is very likely to occur during the preg-nancy. Follistatin related protein 1 precursor may modulate the action of some growth factors on cell proliferation and differentiation. Probable
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RNA-binding protein KIAA0682 has already been identified in the uterus. Dynein heavy chain cytosolic and osteopontin have already been detected in placenta. Keratin type I cytoskeletal 9 has already been found in human placenta. Mesothelin precursor is linked to ovarian activity, and myosin heavy chain, skeletal muscle perinatal is also linked to pregnancy.
In 2007 Cho et al. analyzed the AF proteome and compared the proteins present in AF with proteins from human plasma [64]. By searching the Plasma Proteome Database found that 304 (36%) of the 842 proteins have also been found in plasma and concluded that this does not mean that the remaining 538 proteins are exclusive to AF because the plasma pro-teome list is still growing. Also, several putative markers as well as cur-rently used markers for PROM were found in AF including prolactin, alpha-fetoprotein (AFP), IGFBP-1, fibronectin, agrin, plasma retinol-binding protein precursor, apolipoprotein A-I, B-factor. These proteins have been already mentioned as potential markers in literature. This study identified the new marker candidate for PROM - :OP&I chain.
However, the validation of these proteins as biomarkers of PROM was not done. In order to confirm proteins or peptides as biomarkers of PROM, they should be present in AF, absent in maternal plasma, and should be easily detected in vaginal fluid of patients with PROM. The proteome of normal human cervico-vaginal fluid (CVF) is already established and described in the literature [75,76]. Wang et al. used a protein array to screen amniotic fluid samples and cervical-vaginal fluid collected from normal and PROM pregnant women. Enzyme-linked immunosorbent assay was used to quantify two novel and potentially useful analytes, soluble intercellular adhesion molecule-1 (sICAM-1) and Axl receptor tyrosine kinase (Axl). Comparing 110 CVF samples of PROM/PPROM with 110 CVF samples of normal pregnancies, the diagnostic value for PROM was demonstrated by their high sensitivity and specificity (96.4 and 92.7%, respectively, for sICAM-1, and 92.4% and 90.4%, respectively, for Axl) [77]. sICAM-1 or Axl can be developed into a rapid strip test for bedside use.
No significant relationship, however regarding the sensitivity, speci-ficity and predictive value for the accurate detection of women at risk for PROM has been demonstrated up to now. Though, the analysis shows that proteomics is a valuable approach to gain insight into the physiology of amniotic fluid and to identify new potential biological markers for PROM diagnosis. The data further support the view that quantitative shotgun proteomics analysis of AF may be a feasible and effective method to screen multiple pathologies in the future.
32 4.4.3.2. Amniotic fluid infection
Intraamniotic infection (IAI) is linked with PPROM and preterm birth. Infection of amniotic fluid and membranes has been implicated as the major known cause of PPROM. The presence of IAI strongly associated with the adverse neonatal outcome. Early diagnosis of IAI is problematic, however, because clinical signs and symptoms (including preterm labor or rupture of membranes) tend to be late manifestations of this condition. Furthermore, the available noninvasive diagnostic tests of IAI have limited predictive value. The goal is to discover the sensitive and specific noninvasive test to predict clinically undetectable IAI by proteomic profiling methods.
By using surface-enhanced laser desorption/ionization time of flight MS (SELDI-TOF/MS), gel electrophoresis, and tandem mass spectrometry, Gravett et al. were able to characterize several amniotic fluid peptides in a model of animal infection [78,79]. Markers such as calgranulin B (S100A9), azurocidin, vitamin D binding protein, and insulin-like growth factor binding protein 1 were tested in a cohort of 11 women with occult IAI by liquid chromatography – tandem mass spectrometry. Based on the results of this study, calgranulin B and a proteolytic fragment IGFBP-1 have been proposed as candidate biomarkers for IAI. Similarly, Ruetschi et al. reported that human neutrophil defensins 1-3 and calgranulins A and B are part of the AF fingerprint characteristic of intraamniotic inflammation and/or infection [80]. Park et al. found altered expression of Calgranulin A and B in human amnion and AF samples obtained from pregnant women infected with Ureaplasma urealyticum. The results showed that specific biomarkers in amniotic fluid might have application in the early detection of intraamniotic infection. It is of special interest that the same differences in protein expression were also found in maternal serum, allowing for noninvasive detection of IAI. The role of IGFBP-1 biological activity in IAI was confirmed by Bujold et al. using a combination of techniques involving 2D chromatography, MS and immunoassays too [81]. All data together suggest that the total amount of IGFBP-1 does not change, but that IAI leads to increased proteolytic degradation of IGFBP-1 resulting in an increased con-centration of a fragment of IGFBP-1 (at about 13.5 kDa) [82]. The same study reported protein profile that was over-expressed in amniotic fluid of women with IAI who delivered preterm. Fibrinopeptide B, transferrin, ma-jor histocompatibility complex (MHC) class 1 chainrelated A antigen frag-ment, transcription elongation factor A, sex-determining region Y (SRY) box 5 protein, DSCR2, and HP8 were linked with IAI.
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From 2005 two groups lead by C. Buhimschi and R. Romero mainly investigated the presence of biomarkers of IAI and the relationship with preterm labor (PTL) by proteomics tools. Buhimschi et al. also used surface-enhanced laser desorption/ionization time of flight MS and profiled specific proteins for infection in AF and reported on the existence of four bio-markers, including neutrophil defensins-1 and 2, calgranulins A (A100A8) and C (S100A12). Based on the presence or absence of these biomarkers, they devised the called the „mass restricted (MR) score“ ranging from 0 (all biomarkers absent) to 4 (all biomarkers present) [83]. A MR score >2 was associated with imminent preterm delivery. If no biomarkers are present, then the pregnancy is considered to be uncomplicated while an „MR score“ of three or four is highly predictive of adverse pregnancy outcome. Proteo-mic analysis of amniotic fluid was shown to be the most accurate test for diagnosis of intraamniotic inflammation, whereas addition of the MR score to the Gram stain provides the best combination of tests to rapidly predict infection [84]. The authors observed a sequential appearance of the bio-markers as the process of intraamniotic inflammation developed from acute to chronic, with S100A12 and S100A8 appearing last. In the later studies Buhimchi et al. confirm that high MR scores are associated early onset neonatal sepsis [85,86]. Presence of S100A12 and S100A8 in AF is pre-dictive of early-onset neonatal sepsis and poor neuro-developmental out-come [87]. This methodology shown that proteomic profiling of the AF can rapidly and accurately diagnose IAI, and can identify the subgroup of patients that might benefit most from interventions to prevent fetal damage in utero [88]. The biomarkers comprising the MR score have a unique ability to predict in utero clinically relevant histological chorioamnionitis [89] and funisitis [90], which are known risk factors for sepsis and poor neonatal outcome [91]. Presence in the AF of S100A12 (EN-RAGE, ligand for the advanced glycation end products (RAGE) receptor) [92,93] had the strongest correlation with chorioamnionitis and funisitis.
Romero et al. using liquid chromatography tandem mass spectrometry with isobaric labeling of the AF proteome of women with PTL identified proteins differentially regulated in women with IAI and in those without IAI who delivered preterm [94]. Importantly, many novel proteins were found to be up-regulated in the AF of patients with PTL and IAI including leukocyte elastase precursor, Thymosin-like 3, and 14-3-3 protein isoforms.
