Proteomic technologies for prenatal diagnostics: advances and challenges ahead

Identification of Gravida Serum Biomarkers for Noninvasive Prenatal Diagnosis Fetal Congenital Heart Disease

Congenital heart disease (CHD) is well established as the most common congenital defect worldwide. Given the lack of biomarkers available, we aimed to identify new biomarkers for the noninvasive prenatal diagnosis of fetal CHD. This study used data-independent acquisition (DIA) to explore potential protein biomarkers that co-expressed in gravida serum (GS) and fetal amniotic fluid (AF). Next, parallel reaction monitoring (PRM), enzyme-linked immunosorbent assay (ELISA), receiver operating characteristic curve (ROC) analysis, and the immunohistochemistry (IHC) were performed to validate the potential biomarkers. Based on DIA and PRM proteomics and bioinformatics results, we identified POSTN and PAPPA in GS as candidate biomarkers. Their differential expression during ELISA and IHC were generally consistent with our proteomics results. POSTN combined with PAPPA in GS yield a good diagnose fetal CHD with sensitivity of 83.9%, specificity of 73.9%, and an area under curve (AUC) of 0.842. This is the first study showing that POSTN in GS and AF is associated with fetal CHD. POSTN and PAPPA have huge prospects for application as potential biomarkers in the noninvasive prenatal diagnosis of fetal CHD. Congenital heart disease (CHD) is well-established as the most common congenital defect worldwide. Given the lack of biomarkers available, we aimed to identify new biomarkers for the noninvasive prenatal diagnosis of fetal CHD. We used data independent acquisition (DIA) to explore potential protein biomarkers that co-expressed in gravida serum (GS) and fetal amniotic fluid (AF). Next, parallel reaction monitoring (PRM), enzyme-linked immunosorbent assay (ELISA), receiver operating characteristic curve (ROC) analysis, and the immunohistochemistry (IHC) were performed to validate the potential biomarkers. Based on DIA and PRM proteomics and bioinformatics results, we identified POSTN and PAPPA in GS as candidate biomarkers. Their differential expression during ELISA and IHC were generally consistent with our proteomics results. POSTN combined with PAPPA in GS yield a good diagnose fetal CHD with sensitivity of 83.9 %, specificity of 73.9%, and an area under curve (AUC) of 0.842. This is the first study showing that POSTN in GS and AF is associated with fetal CHD. POSTN and PAPPA have huge prospects for application as potential biomarkers in the noninvasive prenatal diagnosis of fetal CHD.

Comparative Proteomic Assessment of Normal vs. Polyhydramnios Amniotic Fluid Based on Computational Analysis

Mass spectrometry-based proteomics have become a valued tool for conducting comprehensive analyses in amniotic fluid samples with pathologies. Our research interest is the finding and characterization of proteins related to normal vs. polyhydramnios (non-immune hydrops) pregnancy. Proteomic analysis was performed on proteins isolated from fresh amniotic fluid samples. Proteins were fractionated by 2DE using a different pI range (pI 3–11, pI 4–7) and analyzed with MALDI-TOF-MS. Furthermore, by using computational analysis, identified proteins in protein maps specific to normal vs. polyhydramnios pregnancy were compared and the quantities of expressed proteins were evaluated mathematically. Comparative analysis of proteome characteristic for the same polyhydramnios pregnancy fractionated by 2DE in different pI range (3–11 and 4–7) was performed and particular protein groups were evaluated for the quantification of changes within the same protein level. Proteins of normal and polyhydramnios pregnancies were fractionated by 2DE in pI range 3–11 and in pI range 4–7. Mass spectrometry analysis of proteins has revealed that the quantity changes of the main identified proteins in normal vs. polyhydramnios pregnancy could be assigned to immune response and inflammation proteins, cellular signaling and regulation proteins, metabolic proteins, etc. Specifically, we have identified and characterized proteins associated with heart function and circulatory system and proteins associated with abnormalities in prenatal medicine. The following are: serotransferrin, prothrombin, haptoglobin, transthyretin, alpha-1-antitrypsin, zinc-alpha-2-glycprotein, haptoglobin kininogen-1, hemopexin, clusterin, lumican, afamin, gelsolin. By using computational analysis, we demonstrated that some of these proteins increased a few times in pathological pregnancy. Computer assistance analysis of 2DE images suggested that, for the better isolation of the proteins’ isoforms, those levels increased/decreased in normal vs. polyhydramnios pregnancy, and the fractionation of proteins in pI rage 3–11 and 4–7 could be substantial. We analyzed and identified by MS proteins specific for normal and polyhydramnios pregnancies. Identified protein levels increased and/or modification changed in case of non-immune hydrops fetus and in cases of cardiovascular, anemia, growth restriction, and metabolic disorders. Computational analysis for proteomic characterization empower to estimate the quantitative changes of proteins specific for normal vs. polyhydramnios pregnancies.

Identification and Validation of Combination Plasma Biomarker of Afamin, Fibronectin and Sex Hormone-Binding Globulin to Predict Pre-eclampsia

The purpose of the present study was to identify a plasma protein biomarker able to predict pre-eclampsia (PE). Comprehensive quantitative proteomics using mass spectrometry with sequential window acquisition of all theoretical fragment ion spectra (SWATH-MS) was applied to plasma samples of 7 PE and 14 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE), and 11 proteins were selected as candidates potentially able to differentiate the two groups. Plasmas collected at gestational weeks 14-24 from 36 PE and 120 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE) were used to conduct selected reaction monitoring quantification analysis, optimize protein combinations and conduct internal validation, which consisted of 30 iterations of 10-fold cross-validation using multivariate logistic regression and receiver operating characteristic (ROC) analysis. The combination of afamin, fibronectin, and sex-hormone-binding globulin was selected as the best candidate. The 3-protein combination predictive model (predictive equation and cut-off value) generated using the internal validation subjects was successfully validated in another group of validation subjects (36 PE and 54 healthy (for PE subjects, plasma samples were taken before onset of PE)) and showed good predictive performance, with the area under the curve (AUC) 0.835 and odds ratio 13.43. In conclusion, we newly identified a 3-protein combination biomarker and established a predictive equation and cut-off value that can predict the onset of PE based on analysis of plasma samples collected during gestational weeks 14-24.

MULTIOMIC PATTERNS IN BODY FLUIDS: TECHNOLOGICAL CHALLENGE WITH A GREAT POTENTIAL TO IMPLEMENT THE ADVANCED PARADIGM OF 3P MEDICINE

Liquid biopsy (LB) is defined as a sample of any of body fluids (blood, saliva, tear fluid, urine, sweat, amniotic, cerebrospinal and pleural fluids, cervicovaginal secretion, and wound efflux, amongst others), which can be ex vivo analysed to detect and quantity the target(s) of interest. LB represents diagnostic approach relevant for organ-specific changes and systemic health conditions including both manifested diseases and their prestages such as suboptimal health. Further, experts emphasise that DNA-based analysis alone does not provide sufficient information for optimal diagnostics and effective treatments. Consequently, of great scientific and clinical utility are molecular patterns detected by hybrid technologies such as metabolomic tools and molecular imaging. Future proposed strategies utilise multiomic pillars (generally genome, tanscriptome, proteome, metabolome, epigenome, radiome, and microbiome), system-biological approach, and multivariable algorithms for diagnostic, prognostic, and therapeutic purposes. Current article analyses pros and cons of the mass spectrometry-based technologies, provides eminent examples of a success story "from discovery to clinical application," and demonstrates a "road-map" for the technology-driven paradigm change from reactive to predictive, preventive and personalised medical services as the medicine of the future benefiting the patient and healthcare at large. © 2019 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

Prenatal maternal biomarkers for the early diagnosis of congenital malformations: A review

Congenital anomalies cause ~7% of all neonatal deaths, many of which have no identified pathophysiological cause. Because accurate and robust laboratory tests are unavailable for most birth defects, physicians rely on imaging such as ultrasound and MRI. Biomarkers from human body fluids are considered a powerful diagnostic tool to assess human disease and health as it mirrors an individual's condition. Minimally invasive 'liquid biopsies' from blood samples are highly valuable for diagnosis, prognosis, risk assessment, and treatment of many conditions. Recent large-scale analysis ('omics') have enabled researchers to identify novel biomarkers in different areas. To accurately facilitate the early detection of congenital anomalies, the identification of biomarkers from maternal plasma should be promoted. This approach will uncover new opportunities in prenatal diagnosing and likely lead to a better understanding of the pathogenesis of congenital anomalies.

Advances in the proteomics of amniotic fluid to detect biomarkers for chromosomal abnormalities and fetomaternal complications during pregnancy

INTRODUCTION

Amniotic fluid (AF) is a dynamic and complex mixture that reflects the physiological condition of developing fetus. In the last decade, proteomic analysis of AF for 16-18 weeks normal pregnancy has been done for the composition and functions of this fluid. Other body fluids such as urine, sweat, tears, etc. are being used for diagnosis of disease, but an insight into protein biomarkers of amniotic fluid can save the fetus and mother from future complications. Areas covered: We have covered the proteomics of amniotic fluid done since 2000, in order to strengthen the establishment of these techniques as a recognized diagnostic tool in the field. After classifying the diseases based on chromosomal aneuploidies, gestational changes, and inflammation caused during pregnancy; we have focused on amniotic fluid to detect various complications during and post pregnancy and its effect on the fetomaternal relationship. Expert comment: The main protein biomarkers responsible for various syndromes, diseases, and complications have been summarized. Major proteins identified for gestational conditions are IGFBP-1, fibrinogen, neutrophil defensins like calgranulins A and C, cathelicidin, APOA1, TRFE, etc. Validation of particular technique and establishing a single standardized biomarker for the diagnosis to avoid any overlapping for different diseases is required. After certain improvements, proteomics approach can be considered for diagnosis of diseases associated with fetal-maternal health.

Fetal neurology: Principles and practice with a life-course perspective

Clinical service, educational, and research components of a fetal/neonatal neurology program are anchored by the disciplines of developmental origins of health and disease and life-course science as programmatic principles. Prenatal participation provides perspectives on maternal, fetal, and placental contributions to health or disease for fetal and subsequent neonatal neurology consultations. This program also provides an early-life diagnostic perspective for neurologic specialties concerned with brain health and disease throughout childhood and adulthood. Animal models and birth cohort studies have demonstrated how the science of epigenetics helps to understand gene-environment interactions to better predict brain health or disease. Fetal neurology consultations provide important diagnostic contributions during critical or sensitive periods of brain development when future neurotherapeutic interventions will maximize adaptive neuroplasticity. Age-specific normative neuroinformatics databases that employ computer-based strategies to integrate clinical/demographic, neuroimaging, neurophysiologic, and genetic datasets will more accurately identify either symptomatic patients or those at risk for brain disorders who would benefit from preventive, rescue, or reparative treatment choices throughout the life span.

Potential role of "omics" technique in prenatal diagnosis of congenital heart defects

Congenital heart defect (CHD) is one of the most common birth defects and is the leading cause of neonatal death. Currently, there are no biomarkers available for prenatal diagnosis of CHD. Clinical strategies to diagnose CHD mostly depend on fetal echocardiography. Recent advances in "omics" techniques have opened up new possibilities for biomarker discoveries. In this review, we discuss recent advances in prenatal detection of CHD using biomarkers obtained by "omics" approaches, including genomics, proteomics, metabolomics, and others. There is great potential in obtaining various kinds of parameters using "omics" studies to facilitate early and accurate diagnosis of CHD.

Comprehensive maternal serum proteomics identifies the cytoskeletal proteins as non-invasive biomarkers in prenatal diagnosis of congenital heart defects

Congenital heart defects (CHDs) are the most common group of major birth defects. Presently there are no clinically used biomarkers for prenatally detecting CHDs. Here, we performed a comprehensive maternal serum proteomics assessment, combined with immunoassays, for the discovery of non-invasive biomarkers for prenatal diagnosis of CHDs. A total of 370 women were included in this study. An isobaric tagging for relative and absolute quantification (iTRAQ) proteomic approach was used first to compare protein profiles in pooled serum collected from women who had CHD-possessing or normal fetuses, and 47 proteins displayed significant differential expressions. Targeted verifications were performed on 11 proteins using multiple reaction monitoring mass spectrometry (MRM-MS), and the resultant candidate biomarkers were then further validated using ELISA analysis. Finally, we identified a biomarker panel composed of 4 cytoskeletal proteins capable of differentiating CHD-pregnancies from normal ones [with an area under the receiver operating characteristic curve (AUC) of 0.938, P < 0.0001]. The discovery of cytoskeletal protein changes in maternal serum not only could help us in prenatal diagnosis of CHDs, but also may shed new light on CHD embryogenesis studies.

Establishment of a decision tree model for diagnosis of early rheumatoid arthritis by proteomic fingerprinting

AIM

The objective of this study was to identify proteomic biomarkers specific for rheumatoid arthritis (RA) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in combination with weak cationic exchange (WCX) magnetic beads.

METHODS

Serum samples from 50 patients with RA and 110 disease controls (50 SLE and 60 SS) and 51 healthy individuals were analyzed. The samples were randomly divided into a training set or test set to develop a diagnostic model for RA.

RESULTS

A total of 83 protein peaks were identified to be related with RA, in which four of the peaks with mass-charge ratio (m/z) at 8133.85, 5844.60, 13 541.3 and 14 029.0 were selected to establish a model for diagnosis of RA. This classification model could separate patients with RA from diseased and healthy controls with sensitivity of 84.0% and specificity of 92.5%, and its accuracy was confirmed in the blind testing set with high sensitivity and specificity of 80.0% and 93.3%, respectively.

CONCLUSIONS

This study suggested that potential serum biomarkers for RA diagnosis could be discovered by MALDI-TOF-MS. The classification tree model set up in this study might be used as a novel diagnostic tool for RA.

Biomarker development for presymptomatic molecular diagnosis of preeclampsia: feasible, useful or even unnecessary?

The past decade saw the advent of a number of promising biomarkers to detect pregnancies at risk for preeclampsia (PE), the foremost being those associated with an imbalance of angiogenic factors. In late pregnancy, these are useful for the detection of imminent cases of PE, while earlier they were more predictive for early- than late-onset PE. This suggests that there may be fundamental differences between the underlying pathology of these two PE forms. Therefore, it is possible that such a biological premise may limit the development of biomarkers that will permit the efficacious detection of both early- and late-onset PE via an analysis of first-trimester maternal blood samples. Consequently, a significant increase in our understanding of the underlying pathology of PE, using a variety of approaches ranging from systems biology to animal models, will be necessary in order to overcome this obstacle.

Non invasive prenatal diagnosis of aneuploidy: next generation sequencing or fetal DNA enrichment?

Current invasive procedures [amniocentesis and chorionic villus sampling (CVS)] pose a risk to mother and fetus and such diagnostic procedures are available only to high risk pregnancies limiting aneuploidy detection rate. This review seeks to highlight the necessity of investing in non invasive prenatal diagnosis (NIPD) and how NIPD would improve patient safety and detection rate as well as allowing detection earlier in pregnancy. Non invasive prenatal diagnosis can take either a proteomics approach or nucleic acid-based approach; this review focuses on the latter. Since the discovery of cell free fetal DNA (cffDNA) and fetal RNA in maternal plasma, procedures have been developed for detection for monogenic traits and for some have become well established (e.g., RHD blood group status). However, NIPD of aneuploidies remains technically challenging. This review examines currently published literature evaluating techniques and approaches that have been suggested and developed for aneuploidy detection, highlighting their advantages and limitations and areas for further research.

Amniotic fluid: the use of high-dimensional biology to understand fetal well-being

Our aim was to review the use of high-dimensional biology techniques, specifically transcriptomics, proteomics, and metabolomics, in amniotic fluid to elucidate the mechanisms behind preterm birth or assessment of fetal development. We performed a comprehensive MEDLINE literature search on the use of transcriptomic, proteomic, and metabolomic technologies for amniotic fluid analysis. All abstracts were reviewed for pertinence to preterm birth or fetal maturation in human subjects. Nineteen articles qualified for inclusion. Most articles described the discovery of biomarker candidates, but few larger, multicenter replication or validation studies have been done. We conclude that the use of high-dimensional systems biology techniques to analyze amniotic fluid has significant potential to elucidate the mechanisms of preterm birth and fetal maturation. However, further multicenter collaborative efforts are needed to replicate and validate candidate biomarkers before they can become useful tools for clinical practice. Ideally, amniotic fluid biomarkers should be translated to a noninvasive test performed in maternal serum or urine.

Peripartum consultations expand the role of the fetal/neonatal neurologist

The peripartum period entails the next prenatal interval when novel neuroprotective strategies will be designed and tested. Research development will lead to novel evaluations for maternal-fetal pairs who require inpatient treatment and possible delivery for worsening or acute neurologic problems. Future studies should critically compare serial fetal surveillance assessments with postnatal clinical findings to detect and treat more accurately fetal/neonatal brain disorders that begin or worsen during the peripartum period. Clinical management decisions require an interdisciplinary treatment approach. Protocols may begin before and during parturition, and continue through neonatal resuscitation and early postnatal periods into infancy. Appropriate choices of preventive, rescue, and repair neuroprotective interventions must consider both the timing and etiologies of encephalopathies in the context of maternal, fetal, placental, and neonatal diseases.

Longitudinal analysis of maternal plasma apolipoproteins in pregnancy: a targeted proteomics approach

Minimally invasive diagnostic tests are needed in obstetrics to identify women at risk for complications during delivery. The apolipoproteins fluctuate in complexity and abundance in maternal plasma during pregnancy and could be incorporated into a blood test to evaluate this risk. The objective of this study was to examine the relative plasma concentrations of apolipoproteins and their biochemically modified subtypes (i.e. proteolytically processed, sialylated, cysteinylated, dimerized) over gestational time using a targeted mass spectrometry approach. Relative abundance of modified and unmodified apolipoproteins A-I, A-II, C-I, C-II, and C-III was determined by surface-enhanced laser desorption/ionization-time of flight-mass spectrometry in plasma prospectively collected from 11 gravidas with uncomplicated pregnancies at 4-5 gestational time points per patient. Apolipoproteins were readily identifiable by spectral pattern. Apo C-III(2) and Apo C-III(1) (doubly and singly sialylated Apo C-III subtypes) increased with gestational age (r(2)>0.8). Unmodified Apo A-II, Apo C-I, and Apo C-III(0) showed no correlation (r(2) = 0.01-0.1). Pro-Apo C-II did not increase significantly until third trimester (140 ± 13% of first trimester), but proteolytically cleaved, mature Apo C-II increased in late pregnancy (702 ± 130% of first trimester). Mature Apo C-II represented 6.7 ± 0.9% of total Apo C-II in early gestation and increased to 33 ± 4.5% in third trimester. A label-free, semiquantitative targeted proteomics approach was developed using LTQ-Orbitrap mass spectrometry to confirm the relative quantitative differences observed by surface-enhanced laser desorption/ionization-time of flight-mass spectrometry in Apo C-III and Apo C-II isoforms between first and third trimesters. Targeted apolipoprotein screening was applied to a cohort of term and preterm patients. Modified Apo A-II isoforms were significantly elevated in plasma from mothers who delivered prematurely relative to term controls (p = 0.02). These results support a role for targeted proteomics profiling approaches in monitoring healthy pregnancies and assessing risk of adverse obstetric outcomes.

Preliminary proteomic-based identification of a novel protein for Down's syndrome in maternal serum

Prenatal screening for Down's syndrome (DS) is in need of improvement. As a powerful platform, proteomics techniques could also be used for identification of new biomarkers for DS screening. In this case-control proteome study, pregnant women were diagnosed prenatally by karyotype analysis from amniotic fluid (AF). Maternal serum samples were collected from six pregnancies with fetuses affected by DS and six pregnancies with normal fetuses. First, we used two-dimensional electrophoresis and mass spectrometry to identify the different levels of expression of proteins in maternal serum between the DS and control groups in the second trimester. Second, we used bioinformatics to analyze the proteins by DAVID. Then, the interesting candidates were further tested by enzyme-linked immunosorbent assay (ELISA). Twenty-nine proteins were successfully identified in maternal serum obtained from pregnancies with fetuses affected by DS. The top five proteins up-regulated were serotransferrin (TF), alpha-1b-glycoprotein (A1BG), desmin (DES), alpha-1-antitrypsin (SERPINA1) and ceruloplasmin (CP), while serum amyloid P-component (APCS) was the most down-regulated protein. These 29 proteins were categorized based on binding, catalytic activity and enzyme regulator activity. The biological roles were involved in biological regulation, metabolic processes, cellular processes and response to a stimulus. Based on ELISA, the median concentrations of CP and complement factor B (CFB) were 332.3 and 412.3 ng/mL, respectively. The concentrations of CP and CFB were significantly higher in the DS group than in the control group ( P < 0.05). In conclusion, proteomic approaches offer the possibility of further improving the performance of DS screening and our identification of up- and down-regulated proteins may lead to new candidates for DS screening.

An interdisciplinary fetal/neonatal neurology program

A fetal/neonatal neurology program should encompass interdisciplinary service, educational and research objectives, merging curricula concerning maternal, placental, fetal and neonatal contributions to brain health and disease. This approach is anchored by research in early life programming that demonstrates that prenatal and postnatal factors influence long-term neurologic health. This concept also supports the design of neuroprotective interventions during critical periods of brain development when brain circuitries more optimally adapt to maturational challenges. Preventive, rescue and repair protocols will transform pediatric medical practices, to promote improved childhood outcomes. Inclusion of life-course science and research will identify medical and socioeconomic factors that favorably or adversely affect quality of life into adulthood. Greater awareness of the convergence of developmental origins of brain health and disease and developmental aging theories will influence public health policies, to encourage financial support for programs that will improve the quality of life for the child and adult.

Discovery of serum protein biomarkers in rheumatoid arthritis using MALDI-TOF-MS combined with magnetic beads

The aim of this study was to discover potential biomarkers for rheumatoid arthritis (RA) using Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with magnetic beads. Proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS was used to profile and compare the proteomes in serum samples from 60 patients with RA, 35 patients with osteoarthritis and 36 healthy controls. The proteomic pattern associated with RA was identified by Biomarker Patterns Software. Model of biomarkers was constructed and evaluated through the Biomarker Patterns Software. A total of 33 discriminative peaks were identified to be related with RA, in which the 5 peaks with the mass-charge ratio (m/z) peaks at 15,715.5, 7,771.4, 8,959.4, 8,469.8 and 8,710.8 Da were used to construct a model for the diagnosis of RA by pattern recognition software. The blind testing data indicated a sensitivity of 86.7% and a specificity of 90.0% in RA diagnosis. These results demonstrated that potential protein biomarkers for RA could be discovered in serum by MALDI-TOF-MS combined with WCX magnetic beads. The diagnosis mode tree based on the five candidate biomarkers could provide a powerful and reliable diagnostic method for RA with high sensitivity and specificity.

Proteomic analysis of amniotic fluid for the diagnosis of fetal aneuploidies

Advances in technologies associated with mass spectrometry-based proteomic techniques have added a new dimension to the field of biomedical research. Most of the existing research on human gestation has focused on the application of these high-throughput methodologies in the study of amniotic fluid. In cases of fetal aneuploidies, the use of proteomic platforms has contributed to the identification of relevant protein biomarkers that could potentially change early diagnosis and treatment. The current article focuses on studies of normal amniotic fluid using proteomic technologies and describes alterations noted in the amniotic fluid proteome in the presence of fetal aneuploidies.

Determination of fetal chromosome aberrations from fetal DNA in maternal blood: has the challenge finally been met?

The analysis of cell-free fetal nucleic acids in maternal blood for prenatal diagnosis has been transformed by several recent profound technology developments. The most noteworthy of these are 'digital PCR' and 'next-generation sequencing' (NGS), which might finally deliver the long-sought goal of noninvasive detection of fetal aneuploidy. Recent data, however, indicate that NGS might even be able to offer a much more detailed appraisal of the fetal genome, including paternal and maternal inheritance of point mutations for mendelian disorders such as β-thalassaemia. Although these developments are very exciting, in their current form they are still too complex and costly, and will need to be simplified considerably for their optimal translation to the clinic. In this regard, targeted NGS does appear to be a step in the right direction, although this should be seen in the context of ongoing progress with the isolation of fetal cells and with proteomic screening markers.

Surface plasmon resonance biosensor for parallelized detection of protein biomarkers in diluted blood plasma

Surface plasmon resonance (SPR) biosensor for high-throughput screening of protein biomarkers in diluted blood plasma is reported. The biosensor combines a high-resolution SPR imaging sensor and a high-density protein array with low-fouling background. The SPR imaging sensor utilizes polarization contrast and advanced referencing and provides a total of 120 sensing areas (each 200 μm×150 μm). Antibodies are immobilized on the sensing areas via hybridization of antibody-oligonucleotide conjugates to thiolated complementary oligonucleotides microspotted on the sensor surface (DNA-directed immobilization). A low-fouling background is achieved by covalent immobilization of bovine serum albumin to carboxyl-terminated thiols filling the areas among the thiolated oligonucleotides and outside the sensing areas. The biosensor was evaluated for detection of protein biomarkers relevant to cancer diagnostics--human chorionic gonadotropin (hCG) and activated leukocyte cell adhesion molecule (ALCAM) both in buffer and in 10% blood plasma. Limits of detection as low as 45 ng/mL (ALCAM) and 100 ng/mL (hCG) were achieved in blood plasma samples.

Systematic discovery of ectopic pregnancy serum biomarkers using 3-D protein profiling coupled with label-free quantitation

Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serum proteomes were quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker discovery strategy consisting of abundant protein immunodepletion, SDS gels, LC-MS/MS, and label-free quantitation of MS signal intensities identified 70 candidate biomarkers with differences between groups greater than 2.5-fold. Further statistical analyses of peptide quantities were used to select the most promising 12 biomarkers for further study, which included known EP biomarkers, novel EP biomarkers (ADAM12 and ISM2), and five specific isoforms of the pregnancy specific beta-1-glycoprotein family. Technical replicates showed good reproducibility and protein intensities from the label-free discovery analysis compared favorably with reported abundance levels of several known reference serum proteins over at least 3 orders of magnitude. Similarly, relative abundances of candidate biomarkers from the label-free discovery analysis were consistent with relative abundances from pilot validation assays performed for five of the 12 most promising biomarkers using label-free multiple reaction monitoring of both the patient serum pools used for discovery and the individual samples that constituted these pools. These results demonstrate robust, reproducible, in-depth 3-D serum proteome discovery, and subsequent pilot-scale validation studies can be achieved readily using label-free quantitation strategies.

Prenatal diagnosis of fetal aneuploidies: post-genomic developments

Prenatal diagnosis of fetal aneuploidies and chromosomal anomalies is likely to undergo a profound change in the near future. On the one hand this is mediated by new technical developments, such as chromosomal microarrays, which allow a much more precise delineation of minute sub-microscopic chromosomal aberrancies than the classical G-band karyotype. This will be of particular interest when investigating pregnancies at risk of unexplained development delay, intellectual disability or certain forms of autism. On the other hand, great strides have been made in the non-invasive determination of fetal genetic traits, largely through the analysis of cell-free fetal nucleic acids. It is hoped that, with the assistance of cutting-edge tools such as digital PCR or next generation sequencing, the long elusive goal of non-invasive prenatal diagnosis for fetal aneuploidies can finally be attained.

Metabolomics in premature labor: a novel approach to identify patients at risk for preterm delivery

OBJECTIVE

Biomarkers for preterm labor (PTL) and delivery can be discovered through the analysis of the transcriptome (transcriptomics) and protein composition (proteomics). Characterization of the global changes in low-molecular weight compounds which constitute the 'metabolic network' of cells (metabolome) is now possible by using a 'metabolomics' approach. Metabolomic profiling has special advantages over transcriptomics and proteomics since the metabolic network is downstream from gene expression and protein synthesis, and thus more closely reflects cell activity at a functional level. This study was conducted to determine if metabolomic profiling of the amniotic fluid can identify women with spontaneous PTL at risk for preterm delivery, regardless of the presence or absence of intraamniotic infection/inflammation (IAI).

STUDY DESIGN

Two retrospective cross-sectional studies were conducted, including three groups of pregnant women with spontaneous PTL and intact membranes: (1) PTL who delivered at term; (2) PTL without IAI who delivered preterm; and (3) PTL with IAI who delivered preterm. The first was an exploratory study that included 16, 19, and 20 patients in groups 1, 2, and 3, respectively. The second study included 40, 33, and 40 patients in groups 1, 2, and 3, respectively. Amniotic fluid metabolic profiling was performed by combining chemical separation (with gas and liquid chromatography) and mass spectrometry. Compounds were identified using authentic standards. The data were analyzed using discriminant analysis for the first study and Random Forest for the second.

RESULTS

(1) In the first study, metabolomic profiling of the amniotic fluid was able to identify patients as belonging to the correct clinical group with an overall 96.3% (53/55) accuracy; 15 of 16 patients with PTL who delivered at term were correctly classified; all patients with PTL without IAI who delivered preterm neonates were correctly identified as such (19/19), while 19/20 patients with PTL and IAI were correctly classified. (2) In the second study, metabolomic profiling was able to identify patients as belonging to the correct clinical group with an accuracy of 88.5% (100/113); 39 of 40 patients with PTL who delivered at term were correctly classified; 29 of 33 patients with PTL without IAI who delivered preterm neonates were correctly classified. Among patients with PTL and IAI, 32/40 were correctly classified. The metabolites responsible for the classification of patients in different clinical groups were identified. A preliminary draft of the human amniotic fluid metabolome was generated and found to contain products of the intermediate metabolism of mammalian cells and xenobiotic compounds (e.g. bacterial products and Salicylamide).

CONCLUSION

Among patients with spontaneous PTL with intact membranes, metabolic profiling of the amniotic fluid can be used to assess the risk of preterm delivery in the presence or absence of infection/inflammation.

Classification of genes and putative biomarker identification using distribution metrics on expression profiles

Background

Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers.

Methodology/Principal Findings

In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic), and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as ‘brain group’ and ‘non-brain group’; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes.

Conclusions/Significance

The methodology employed here may be used to facilitate disease-specific biomarker discovery.

Proteomics of bacterial pathogenicity: therapeutic implications

Identification of the molecular mechanisms of host-pathogen interaction is becoming a key focus of proteomics. Analysis of these interactions holds promise for significant developments in the identification of new therapeutic strategies to combat infectious diseases, a process that will also benefit parallel improvements in molecular diagnostics, biomarker identification and drug discovery. This review highlights recent advances in functional proteomics initiatives in infectious disease with emphasis on studies undertaken within physiologically relevant parameters that enable identification of the infectious proteome rather than that of the vegetative state. Deciphering the molecular details of what constitutes physiologically relevant host-pathogen interactions remains an underdeveloped aspect of research into infectious disease. The magnitude of this deficit will be largely influenced by the ease with which model systems can be established to investigate such interactions. As the selective pressures exerted by the host on an infecting pathogen are numerous, the adequacy of certain model systems should be considered carefully.