Effects of continuity of care by a primary midwife (caseload midwifery) on caesarean section rates in women of low obstetric risk: the COSMOS randomised controlled trial

OBJECTIVE

To determine whether primary midwife care (caseload midwifery) decreases the caesarean section rate compared with standard maternity care.

DESIGN

Randomised controlled trial.

SETTING

Tertiary-care women's hospital in Melbourne, Australia.

POPULATION

A total of 2314 low-risk pregnant women.

METHODS

Women randomised to caseload received antenatal, intrapartum and postpartum care from a primary midwife with some care by 'back-up' midwives. Women randomised to standard care received either midwifery or obstetric-trainee care with varying levels of continuity, or community-based general practitioner care.

MAIN OUTCOME MEASURES

PRIMARY OUTCOME

caesarean birth. Secondary outcomes included instrumental vaginal births, analgesia, perineal trauma, induction of labour, infant admission to special/neonatal intensive care, gestational age, Apgar scores and birthweight.

RESULTS

In total 2314 women were randomised-1156 to caseload and 1158 to standard care. Women allocated to caseload were less likely to have a caesarean section (19.4% versus 24.9%; risk ratio [RR] 0.78; 95% CI 0.67-0.91; P = 0.001); more likely to have a spontaneous vaginal birth (63.0% versus 55.7%; RR 1.13; 95% CI 1.06-1.21; P < 0.001); less likely to have epidural analgesia (30.5% versus 34.6%; RR 0.88; 95% CI 0.79-0.996; P = 0.04) and less likely to have an episiotomy (23.1% versus 29.4%; RR 0.79; 95% CI 0.67-0.92; P = 0.003). Infants of women allocated to caseload were less likely to be admitted to special or neonatal intensive care (4.0% versus 6.4%; RR 0.63; 95% CI 0.44-0.90; P = 0.01). No infant outcomes favoured standard care.

CONCLUSION

In settings with a relatively high baseline caesarean section rate, caseload midwifery for women at low obstetric risk in early pregnancy shows promise for reducing caesarean births.

Life's simple measures: unlocking the proteome

Using modified nucleotides and selecting for slow off-rates in the SELEX procedure, we have evolved a special class of aptamers, called SOMAmers (slow off-rate modified aptamers), which bind tightly and specifically to proteins in body fluids. We use these in a novel assay that yields 1:1 complexes of the SOMAmers with their cognate proteins in body fluids. Measuring the SOMAmer concentrations of the resultant complexes reflects the concentration of the proteins in the fluids. This is simply done by hybridization to complementary sequences on solid supports, but it can also be done by any other DNA quantification technology (including NexGen sequencing). We use measurements of over 1000 proteins in under 100 μL of serum or plasma to answer important medical questions, two of which are reviewed here. A number of bioinformatics methods have guided our discoveries, including principal component analysis. We use various methods to evaluate sample handling procedures in our clinical samples and can identify many parameters that corrupt proteomics analysis.

Protein signature of lung cancer tissues

Lung cancer remains the most common cause of cancer-related mortality. We applied a highly multiplexed proteomic technology (SOMAscan) to compare protein expression signatures of non small-cell lung cancer (NSCLC) tissues with healthy adjacent and distant tissues from surgical resections. In this first report of SOMAscan applied to tissues, we highlight 36 proteins that exhibit the largest expression differences between matched tumor and non-tumor tissues. The concentrations of twenty proteins increased and sixteen decreased in tumor tissue, thirteen of which are novel for NSCLC. NSCLC tissue biomarkers identified here overlap with a core set identified in a large serum-based NSCLC study with SOMAscan. We show that large-scale comparative analysis of protein expression can be used to develop novel histochemical probes. As expected, relative differences in protein expression are greater in tissues than in serum. The combined results from tissue and serum present the most extensive view to date of the complex changes in NSCLC protein expression and provide important implications for diagnosis and treatment.

Aptamers and the RNA world, past and present

Aptamers and the SELEX process were discovered over two decades ago. These discoveries have spawned a productive academic and commercial industry. The collective results provide insights into biology, past and present, through an in vitro evolutionary exploration of the nature of nucleic acids and their potential roles in ancient life. Aptamers have helped usher in an RNA renaissance. Here we explore some of the evolution of the aptamer field and the insights it has provided for conceptualizing an RNA world, from its nascence to our current endeavor employing aptamers in human proteomics to discover biomarkers of health and disease.

Advances in human proteomics at high scale with the SOMAscan proteomics platform

In 1997, while still working at NeXstar Pharmaceuticals, several of us made a proteomic bet. We thought then, and continue to think, that proteomics offers a chance to identify disease-specific biomarkers and improve healthcare. However, interrogating proteins turned out to be a much harder problem than interrogating nucleic acids. Consequently, the 'omics' revolution has been fueled largely by genomics. High-scale proteomics promises to transform medicine with personalized diagnostics, prevention, and treatment. We have now reached into the human proteome to quantify more than 1000 proteins in any human matrix - serum, plasma, CSF, BAL, and also tissue extracts - with our new SOMAmer-based proteomics platform. The surprising and pleasant news is that we have made unbiased protein biomarker discovery a routine and fast exercise. The downstream implications of the platform are substantial.

High-content affinity-based proteomics: unlocking protein biomarker discovery

Single protein biomarkers measured with antibody-based affinity assays are the basis of molecular diagnostics in clinical practice today. There is great hope in discovering new protein biomarkers and combinations of protein biomarkers for advancing medicine through monitoring health, diagnosing disease, guiding treatment, and developing new therapeutics. The goal of high-content proteomics is to unlock protein biomarker discovery by measuring many (thousands) or all (∼23,000) proteins in the human proteome in an unbiased, data-driven approach. High-content proteomics has proven technically difficult due to the diversity of proteins, the complexity of relevant biological samples, such as blood and tissue, and large concentration ranges (in the order of 10(12) in blood). Mass spectrometry and affinity methods based on antibodies have dominated approaches to high-content proteomics. For technical reasons, neither has achieved adequate simultaneous performance and high-content. Here we review antibody-based protein measurement, multiplexed antibody-based protein measurement, and limitations of antibodies for high-content proteomics due to their inherent cross-reactivity. Finally, we review a new affinity-based proteomic technology developed from the ground up to solve the problem of high content with high sensitivity and specificity. Based on a new generation of slow off-rate modified aptamers (SOMAmers), this technology is unlocking biomarker discovery.

Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer

Background

Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease.

Methodology/Principal Findings

We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES) that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC.

Conclusions/Significance

This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels. Separate verification of classifier performance provides evidence against over-fitting and is encouraging for the next development phase, independent validation. This careful study provides a solid foundation to develop tests sorely needed to identify early stage lung cancer.

Aptamer-based multiplexed proteomic technology for biomarker discovery

BACKGROUND

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.

METHODOLOGY/PRINCIPAL FINDINGS

We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.

CONCLUSIONS/SIGNIFICANCE

We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Automation of the SomaLogic Proteomics Assay: A Platform for Biomarker Discovery

At SomaLogic, we have embarked on an ambitious program of clinical studies using a novel aptamerbased proteomics technology to discover biomarkers and develop new tools to diagnose, understand, and treat human disease. As part of this program, we designed and implemented an automated assay for its highly multiplexed proteomics discovery platform. The performance of the automated assay was validated in a study that compared the automated assay to the specifications of an established manual method. Results showed that the automated method performed to the required specifications, and that the automation system improved the efficiency, productivity, and economics of our biomarker discovery program.

A community standard format for the representation of protein affinity reagents

Protein affinity reagents (PARs), most commonly antibodies, are essential reagents for protein characterization in basic research, biotechnology, and diagnostics as well as the fastest growing class of therapeutics. Large numbers of PARs are available commercially; however, their quality is often uncertain. In addition, currently available PARs cover only a fraction of the human proteome, and their cost is prohibitive for proteome scale applications. This situation has triggered several initiatives involving large scale generation and validation of antibodies, for example the Swedish Human Protein Atlas and the German Antibody Factory. Antibodies targeting specific subproteomes are being pursued by members of Human Proteome Organisation (plasma and liver proteome projects) and the United States National Cancer Institute (cancer-associated antigens). ProteomeBinders, a European consortium, aims to set up a resource of consistently quality-controlled protein-binding reagents for the whole human proteome. An ultimate PAR database resource would allow consumers to visit one on-line warehouse and find all available affinity reagents from different providers together with documentation that facilitates easy comparison of their cost and quality. However, in contrast to, for example, nucleotide databases among which data are synchronized between the major data providers, current PAR producers, quality control centers, and commercial companies all use incompatible formats, hindering data exchange. Here we propose Proteomics Standards Initiative (PSI)-PAR as a global community standard format for the representation and exchange of protein affinity reagent data. The PSI-PAR format is maintained by the Human Proteome Organisation PSI and was developed within the context of ProteomeBinders by building on a mature proteomics standard format, PSI-molecular interaction, which is a widely accepted and established community standard for molecular interaction data. Further information and documentation are available on the PSI-PAR web site.

Prevalence of multiple sclerosis in Buenos Aires, Argentina using the capture-recapture method

BACKGROUND

Scarce data exist about multiple sclerosis (MS) prevalence in South America. The objective of the study is to determine the prevalence of MS in a high populated area from Argentina (Greater Buenos Aires Metropolitan area) using the capture-recapture methodology.

METHODS

Greater Buenos Aires is the generic denomination that refers to the megalopolis comprised by the autonomous city of Buenos Aires and the surrounding conurbation of the province of Buenos Aires. The study was carried out taking July 1996 as the prevalence month. We used capture-recapture method to estimate the prevalence of MS cross matching registries from four MS Centers.

RESULTS

A total of 803 registries were obtained from the four lists. Log-linear model for capture-recapture method was used to analyze the data. The population of the area based on the 1990 census was 12,594,974; the number of MS cases estimated amongst sources interactions were between 1833 and 2359; the prevalence estimated ranged from 14 to 19.8 cases per 100,000 inhabitants.

CONCLUSIONS

This is the first study to provide epidemiological data on the prevalence of MS in a large population in Argentina (Greater Buenos Aires Metropolitan area). Further epidemiological studies will clarify the true prevalence of MS in South America.

Site of the ischemic penumbra as a predictor of potential for recovery of functions

BACKGROUND AND PURPOSE

Diffusion-perfusion mismatch has been used to estimate salvageable tissue and predict potential for recovery in acute stroke. Location of the salvageable tissue may be as important as volume or percentage in predicting potential for recovery of specific functions. Impaired naming, a common and disabling deficit after left hemisphere stroke, is often associated with tissue dysfunction of left Brodmann area (BA) 37, posterior inferior temporal cortex. We tested the hypothesis that the presence of diffusion-perfusion mismatch within left BA 37 predicts probability and extent of short-term improvement of naming.

METHODS

One hundred five patients with acute left hemisphere ischemic stroke had diffusion-weighted imaging, perfusion-weighted imaging, a test of picture naming, and other language tests at admission and 2 to 4 days later. Linear regression was used to determine whether diffusion-perfusion mismatch in any BA in language cortex, total volume of mismatch, or diffusion or perfusion abnormality predicted degree of improvement in naming by days 3 to 5.

RESULTS

The presence of >20% diffusion-perfusion mismatch in left BA 37 and total volumes of diffusion and perfusion abnormality at day 1 each independently predicted degree of improvement in naming. Mismatch in this area did not predict the degree of improvement in other language tests or the NIH Stroke Scale in this study.

CONCLUSIONS/RELEVANCE

Diffusion-perfusion mismatch in left Brodmann area 37 was strongly associated with acute improvement in naming, independently of volume or percentage of total mismatch or diffusion or perfusion abnormality. These data indicate that mismatch in a particular area is a marker of salvageable tissue and an important predictor of potential for recovery of functions that depend on that area. Location of mismatch before treatment may help to predict potential benefits of reperfusion.

Argentine Patagonia: prevalence and clinical features of multiple sclerosis

There are few studies reporting multiple sclerosis prevalence rates in the Buenos Aires region, Argentina (latitude 34°S) (between 12–18.5/100 000 inhabitants), and no studies have been performed in the larger region between parallels 36° and 55°S. The aim of this study is to determine the prevalence rates and clinical features of multiple sclerosis in residents of the Argentine Patagonia. Four cities from the region were selected for this study, giving a sample population of 417 666 inhabitants (~24% of the total Patagonia population). 1st March 2002 was determined as prevalence day. Patients were ascertained using multiple case-finding methods. The point prevalence rate was 17.2/100 000 (17.2 age-adjusted to the world population). Prevalence rates were higher for women than for men, 22.1 versus 12.2/100 000 inhabitants (21.4 versus 12.7 sex-adjusted to the world population). The study population was mainly of European descent and mestizoes. Clinical features were similar to those reported in other countries. This study shows that Argentine Patagonia is a medium-risk area with no south–north gradient between parallels 55° and 36°S. The Patagonia population shows recent internal migration that makes it difficult to determine whether the exposure to potential risk factors has been long enough to modify the disease incidence.

Theoretical principles of in vitro selection using combinatorial nucleic acid libraries

A new paradigm for drug discovery and biological research has developed from technologies that integrate combinatorial chemistry with rounds of selection and amplification, a technique called in vitro selection or systematic evolution of ligands by exponential enrichment (SELEX). This overview unit discusses nucleic acid libraries that can be used, affinity probability distributions, an equilibrium model for SELEX, and optimal conditions including concentrations and signal-to-noise ratios.

ProteomeBinders: planning a European resource of affinity reagents for analysis of the human proteome

ProteomeBinders is a new European consortium aiming to establish a comprehensive resource of well-characterized affinity reagents, including but not limited to antibodies, for analysis of the human proteome. Given the huge diversity of the proteome, the scale of the project is potentially immense but nevertheless feasible in the context of a pan-European or even worldwide coordination.

Outcome data from the LEAP (Live, Eat and Play) trial: a randomized controlled trial of a primary care intervention for childhood overweight/mild obesity

OBJECTIVES

To reduce gain in body mass index (BMI) in overweight/mildly obese children in the primary care setting.

DESIGN

Randomized controlled trial (RCT) nested within a baseline cross-sectional BMI survey.

SETTING

Twenty nine general practices, Melbourne, Australia.

PARTICIPANTS

(1) BMI survey: 2112 children visiting their general practitioner (GP) April-December 2002; (2) RCT: individually randomized overweight/mildly obese (BMI z-score <3.0) children aged 5 years 0 months-9 years 11 months (82 intervention, 81 control).

INTERVENTION

Four standard GP consultations over 12 weeks, targeting change in nutrition, physical activity and sedentary behaviour, supported by purpose-designed family materials.

MAIN OUTCOME MEASURES

Primary: BMI at 9 and 15 months post-randomization. Secondary: Parent-reported child nutrition, physical activity and health status; child-reported health status, body satisfaction and appearance/self-worth.

RESULTS

Attrition was 10%. The adjusted mean difference (intervention-control) in BMI was -0.2 kg/m(2) (95% CI: -0.6 to 0.1; P=0.25) at 9 months and -0.0 kg/m(2) (95% CI: -0.5 to 0.5; P=1.00) at 15 months. There was a relative improvement in nutrition scores in the intervention arm at both 9 and 15 months. There was weak evidence of an increase in daily physical activity in the intervention arm. Health status and body image were similar in the trial arms.

CONCLUSIONS

This intervention did not result in a sustained BMI reduction, despite the improvement in parent-reported nutrition. Brief individualized solution-focused approaches may not be an effective approach to childhood overweight. Alternatively, this intervention may not have been intensive enough or the GP training may have been insufficient; however, increasing either would have significant cost and resource implications at a population level.

Photoaptamer arrays applied to multiplexed proteomic analysis

Multiplexed photoaptamer-based arrays that allow for the simultaneous measurement of multiple proteins of interest in serum samples are described. Since photoaptamers covalently bind to their target analytes before fluorescent signal detection, the arrays can be vigorously washed to remove background proteins, providing the potential for superior signal-to-noise ratios and lower limits of quantification in biological matrices. Data are presented here for a 17-plex photoaptamer array exhibiting limits of detection below 10 fM for several analytes including interleukin-16, vascular endothelial growth factor, and endostatin and able to measure proteins in 10% serum samples. The assays are simple, scalable, and reproducible. Affinity of the capture reagent is shown to be directly correlated to the limit of detection for the analyte on the array.

A tenascin-C aptamer identified by tumor cell SELEX: systematic evolution of ligands by exponential enrichment

The targeting of molecular repertoires to complex systems rather than biochemically pure entities is an accessible approach that can identify proteins of biological interest. We have probed antigens presented by a monolayer of tumor cells for their ability to interact with a pool of aptamers. A glioblastoma-derived cell line, U251, was used as the target for systematic evolution of ligands by exponential enrichment by using a single-stranded DNA library. We isolated specifically interacting oligonucleotides, and biochemical strategies were used to identify the protein target for one of the aptamers. Here we characterize the interaction of the DNA aptamer, GBI-10, with tenascin-C, an extracellular protein found in the tumor matrix. Tenascin-C is believed to be involved in both embryogenesis and oncogenesis pathways. Systematic evolution of ligands by exponential enrichment appears to be a successful strategy for the a priori identification of targets of biological interest within complex systems.