Predictive Value of SLCO1B1 c.521T>C Polymorphism on Observed Changes in the Treatment of 1136 Statin-Users.

Pharmacogenomic testing is a method to prevent adverse drug reactions. Pharmacogenomics could be relevant to optimize statin treatment, by identifying patients at high risk for adverse drug reactions. We aim to investigate the clinical validity and utility of pre-emptive pharmacogenomics screening in primary care, with SLCO1B1 c.521T>C as a risk factor for statin-induced adverse drug reactions. The focus was on changes in therapy as a proxy for adverse drug reactions observed in statin-users in a population-based Dutch cohort. In total, 1136 statin users were retrospectively genotyped for the SLCO1B1 c.521T>C polymorphism (rs4149056) and information on their statin dispensing was evaluated as cross-sectional research. Approximately half of the included participants discontinued or switched their statin treatment within three years. In our analyses, we could not confirm an association between the SLCO1B1 c.521T>C genotype and any change in statin therapy or arriving at a stable dose sooner in primary care. To be able to evaluate the predictive values of SLCO1B1 c.521T>C genotype on adverse drug reactions from statins, prospective data collection of actual adverse drug reactions and reasons to change statin treatment should be facilitated.

Expanded Neonatal Bloodspot Screening Programmes: An Evaluation Framework to Discuss New Conditions With Stakeholders.

Neonatal bloodspot screening (NBS) programmes that screen for rare but serious conditions are expanding worldwide. Fast developments for testing and treatment put pressure on implementation processes. In 2015 the Netherlands embarked on an NBS expansion from 17 to 31 conditions. An evaluation framework was developed based on international NBS frameworks to gain insight in test properties, clinical findings, follow-up and implementation. A stakeholder process took place with implications for the planning of the expanded NBS panel. The evaluation framework progressed into a go/no go framework to start national screening, and is currently explored as basis for continuous evaluation of the NBS panel. The framework and stakeholder process may serve as an example for other programmes.

Uptake of fetal aneuploidy screening after the introduction of the non-invasive prenatal test: A national population-based register study.

INTRODUCTION: The introduction of the non-invasive prenatal test (NIPT) has shifted the prenatal screening landscape. Countries are exploring ways to integrate NIPT in their national prenatal screening programs, either as a first- or second-tier test. This study aimed to describe how the uptake of fetal aneuploidy screening changed after the introduction of NIPT as a second-tier and as a first-tier test within the national prenatal screening program of the Netherlands. MATERIAL AND METHODS: A population-based register study in the Netherlands, recording uptake of fetal aneuploidy screening. Data from all pregnant women choosing to have the first-trimester combined test (FCT) or first-tier NIPT between January 2007 and March 2019 were retrospectively collected using national registration systems. Uptake percentages for fetal aneuploidy screening (FCT and NIPT) were calculated and stratified by region and maternal age. Statistical significance was determined using trend analysis and chi-squared tests. RESULTS: Between 2007 and 2013 FCT uptake increased from 14.8% to 29.5% (P = .004). In April 2014 NIPT was introduced as a second-tier test for high-risk women after FCT (TRIDENT-1 study). FCT uptake rose from 29.5% in 2013 to 34.2% in 2015 (P < .0001). After the introduction of NIPT as a first-tier test for all women in April 2017 (TRIDENT-2 study), FCT uptake declined significantly from 35.8% in 2016 to 2.6% in 2018 (P < .0001). NIPT uptake increased to 43.4% in 2018. Regionally, NIPT uptake ranged from 31.8% to 67.9%. Total uptake (FCT and NIPT) between 2007 and 2018 increased significantly from 14.8% to 45.9% (P < .0001). However, total uptake stabilized at 46% for both years of TRIDENT-2 (April 2017-March 2019). CONCLUSIONS: An increase in total fetal aneuploidy screening uptake up to 45.9% was observed after the introduction of NIPT. Uptake appears to have stabilized within a year after introducing first-tier NIPT.

Implementation of Pharmacogenetics in Primary Care: A Multi-Stakeholder Perspective.

INTRODUCTION: Aberrant pharmacogenetic variants occur in a high proportion of people and might be relevant for the prescription of over 26 drugs in primary care. Early identification of patients who metabolize these drugs more rapidly or slowly than average could predict therapeutic effectivity and safety. Yet implementation of pharmacogenetics is progressing slowly. A high public health impact can potentially be achieved by increasing the proportion of people tested, when and where eligible according to clinical validity and utility. METHODS: In this study we defined actions, roles, and responsibilities for implementation of pharmacogenetics in primary care in consultation with stakeholder groups, by using a three-step mixed-methods approach. First, to define barriers and facilitators, public pharmacists (n = 24), primary care physicians (n = 8), and patients (n = 21) participated in focus groups and face-to-face interviews. Second, a multidisciplinary expert meeting (n = 16) was organized to define desired actions, roles, and responsibilities. Third, an online Delphi Study (n = 18) was conducted to prioritize the designated actions. RESULTS: For the integration of pharmacogenetics in primary care guidelines and practice, lack of evidence for clinical utility was mentioned as a main barrier. Furthermore, reimbursement, and facilitation of data registration and sharing were considered as key elements for future routine application of pharmacogenetic testing. Moreover, the division of roles and responsibilities, especially between general practitioners and pharmacists, is currently perceived as unclear. Sixteen actions in these four areas (clinical utility, reimbursement, data registration and sharing, and roles and responsibilities) were formulated and assigned to specific actors during the expert meeting. After ranking these 16 actions in the Delphi Study, nine actions remained pertinent, covering the four areas with at least one action. However, participants showed low agreement on the prioritization of the different actions, illustrating their different perspectives and the need to attune between them. DISCUSSION: Stakeholders together were able to formulate required actions to achieve true integration of pharmacogenetics in primary care, but no consensus could be achieved on the prioritization of the actions. Coordination of the current independent initiatives by the different stakeholders could facilitate effective and efficient implementation of useful pharmacogenetics in primary care.

First trimester placental vascularization and angiogenetic factors are associated with adverse pregnancy outcome.

BACKGROUND: Hypertensive disorders, fetal growth restriction and preterm birth are major obstetrical complications and are related to impaired placentation. Early identification of impaired placentation can advance clinical care by preventing or postpone adverse pregnancy outcome. OBJECTIVES: Determine whether sonographic assessed placental vascular development and concomitant changes in inflammation- and/or angiogenesis-related serumproteins differ in the first trimester between uncomplicated pregnancies and pregnancies with adverse outcome. STUDY DESIGN: This prospective longitudinal study defines adverse pregnancy outcome as conditions associated with impaired placentation; fetal growth restriction, hypertensive disorder, preterm birth and placental abruption. The vascularization index, flow index, vascularization flow index and placental volume were determined at 8, 10 and 12 weeks pregnancy from 64 women using 3D power Doppler. Serum levels were analyzed for Angiopoetin-1 and -2, Leptin, VEGF-R, VEGF, and EGF. RESULTS: The vascularization index and vascular flow index increased in uneventful pregnancies with almost 50% between 8 and 12 weeks, resulting in a ∼50% higher vascularization index at 12 weeks compared to women with an adverse pregnancy outcome. Women with an adverse pregnancy outcome (n = 13) had significantly lower indices and placental volumes at all time points measured and these indices did not increase between 8 and 12 weeks. Reduced vascular development was associated with increased Angiopoietin-1 levels at 8 and 12 weeks and increased Leptin levels at 8 weeks. CONCLUSIONS: Pregnancies with an adverse outcome caused by conditions associated with impaired placentation differ from uneventful pregnancies in having reduced placental vascularization accompanied by elevated circulating levels of Angiopoietin-1 and Leptin already in the first trimester.

The Relationship Between Shift Work and Metabolic Risk Factors: A Systematic Review of Longitudinal Studies.

CONTEXT: Although the metabolic health effects of shift work have been extensively studied, a systematic synthesis of the available research is lacking. This review aimed to systematically summarize the available evidence of longitudinal studies linking shift work with metabolic risk factors. EVIDENCE ACQUISITION: A systematic literature search was performed in 2015. Studies were included if (1) they had a longitudinal design; (2) shift work was studied as the exposure; and (3) the outcome involved a metabolic risk factor, including anthropometric, blood glucose, blood lipid, or blood pressure measures. EVIDENCE SYNTHESIS: Eligible studies were assessed for their methodologic quality in 2015. A best-evidence synthesis was used to draw conclusions per outcome. Thirty-nine articles describing 22 studies were included. Strong evidence was found for a relation between shift work and increased body weight/BMI, risk for overweight, and impaired glucose tolerance. For the remaining outcomes, there was insufficient evidence. CONCLUSIONS: Shift work seems to be associated with body weight gain, risk for overweight, and impaired glucose tolerance. Overall, lack of high-methodologic quality studies and inconsistency in findings led to insufficient evidence in assessing the relation between shift work and other metabolic risk factors. To strengthen the evidence, more high-quality longitudinal studies that provide more information on the shift work schedule (e.g., frequency of night shifts, duration in years) are needed. Further, research to the (mediating) role of lifestyle behaviors in the health effects of shift work is recommended, as this may offer potential for preventive strategies.

Confounding Factors in the Transcriptome Analysis of an In-Vivo Exposure Experiment.

CONFOUNDING FACTORS: In transcriptomics experimentation, confounding factors frequently exist alongside the intended experimental factors and can severely influence the outcome of a transcriptome analysis. Confounding factors are regularly discussed in methodological literature, but their actual, practical impact on the outcome and interpretation of transcriptomics experiments is, to our knowledge, not documented. For instance, in-vivo experimental factors; like Individual, Sample-Composition and Time-of-Day are potentially formidable confounding factors. To study these confounding factors, we designed an extensive in-vivo transcriptome experiment (n = 264) with UVR exposure of murine skin containing six consecutive samples from each individual mouse (n = 64). ANALYSIS APPROACH: Evaluation of the confounding factors: Sample-Composition, Time-of-Day, Handling-Stress, and Individual-Mouse resulted in the identification of many genes that were affected by them. These genes sometimes showed over 30-fold expression differences. The most prominent confounding factor was Sample-Composition caused by mouse-dependent skin composition differences, sampling variation and/or influx/efflux of mobile cells. Although we can only evaluate these effects for known cell type specifically expressed genes in our complex heterogeneous samples, it is clear that the observed variations also affect the cumulative expression levels of many other non-cell-type-specific genes. ANOVA: ANOVA analysis can only attempt to neutralize the effects of the well-defined confounding factors, such as Individual-Mouse, on the experimental factors UV-Dose and Recovery-Time. Also, by definition, ANOVA only yields reproducible gene-expression differences, but we found that these differences were very small compared to the fold changes induced by the confounding factors, questioning the biological relevance of these ANOVA-detected differences. Furthermore, it turned out that many of the differentially expressed genes found by ANOVA were also present in the gene clusters associated with the confounding factors. CONCLUSION: Hence our overall conclusion is that confounding factors have a major impact on the outcome of in-vivo transcriptomics experiments. Thus the set-up, analysis, and interpretation of such experiments should be approached with the utmost prudence.

[Pharmacogenetics in primary health care: implementation and future expectations]. / Farmacogenetica in de eerstelijnszorg: toepassing en toekomstverwachtingen.

Personalised medicine is a targeted approach to the prevention, diagnosis and treatment of disorders on the basis of the specific genetic profile of the patient. Pharmacogenetics research shows that differences in the genetic profile of patients explain the interindividual differences in efficacy and side effects of medicines. Although there are high expectations of personalised medicine and pharmacogenetics in healthcare, both are only used to a limited extent to date. Pharmacogenetics seems particularly important in diseases with a poor prognosis and treatments with potentially serious side effects. Pharmacogenetics testing is reimbursed in the case of serious side effects or unexpected ineffectiveness. 95% of patients in the Netherlands have at least one abnormality in the panel of genes for which guidance is available. The KNMP (Royal Dutch Pharmacists' Association) provides dosing advice based on genotype for 80 medicines, 27 of which are regularly prescribed in primary health care.

Diurnal Variation of Hormonal and Lipid Biomarkers in a Molecular Epidemiology-Like Setting.

INTRODUCTION: Many molecular epidemiology studies focusing on high prevalent diseases, such as metabolic disorders and cancer, investigate metabolic and hormonal markers. In general, sampling for these markers can occur at any time-point during the day or after an overnight fast. However, environmental factors, such as light exposure and food intake might affect the levels of these markers, since they provide input for the internal time-keeping system. When diurnal variation is larger than the inter-individual variation, time of day should be taken into account. Importantly, heterogeneity in diurnal variation and disturbance of circadian rhythms among a study population might increasingly occur as a result of our increasing 24/7 economy and related variation in exposure to environmental factors (such as light and food). AIM: The aim of the present study was to determine whether a set of often used biomarkers shows diurnal variation in a setting resembling large molecular epidemiology studies, i.e., non-fasted and limited control possibilities for other environmental influences. RESULTS: We show that markers for which diurnal variation is not an issue are adrenocorticotropic hormone, follicle stimulating hormone, estradiol and high-density lipoprotein. For all other tested markers diurnal variation was observed in at least one gender (cholesterol, cortisol, dehydroepiandrosterone sulfate, free fatty acids, low-density lipoprotein, luteinizing hormone, prolactin, progesterone, testosterone, triglycerides, total triiodothyronine and thyroid-stimulating hormone) or could not reliably be detected (human growth hormone). DISCUSSION: Thus, studies investigating these markers should take diurnal variation into account, for which we provide some options. Furthermore, our study indicates the need for investigating diurnal variation (in literature or experimentally) before setting up studies measuring markers in routine and controlled settings, especially since time-of-day likely matters for many more markers than the ones investigated in the present study.

Chronically Alternating Light Cycles Increase Breast Cancer Risk in Mice.

Although epidemiological studies in shift workers and flight attendants have associated chronic circadian rhythm disturbance (CRD) with increased breast cancer risk, causal evidence for this association is lacking. Several scenarios have been proposed to contribute to the shift work-cancer connection: (1) internal desynchronization, (2) light at night (resulting in melatonin suppression), (3) sleep disruption, (4) lifestyle disturbances, and (5) decreased vitamin D levels due to lack of sunlight. The confounders inherent in human field studies are less problematic in animal studies, which are therefore a good approach to assess the causal relation between circadian disturbance and cancer. However, the experimental conditions of many of these animal studies were far from the reality of human shift workers. For example, some involved xenografts (addressing tumor growth rather than cancer initiation and/or progression), chemically induced tumor models, or continuous bright light exposure, which can lead to suppression of circadian rhythmicity. Here, we have exposed breast cancer-prone p53(R270H/+)WAPCre conditional mutant mice (in a FVB genetic background) to chronic CRD by subjecting them to a weekly alternating light-dark (LD) cycle throughout their life. Animals exposed to the weekly LD inversions showed a decrease in tumor suppression. In addition, these animals showed an increase in body weight. Importantly, this study provides the first experimental proof that CRD increases breast cancer development. Finally, our data suggest internal desynchronization and sleep disturbance as mechanisms linking shift work with cancer development and obesity.

Predictive performance of a seven-plex antibody array in prenatal screening for Down Syndrome.

We evaluated the use of multiplex antibody array methodology for simultaneous measurement of serum protein markers for first trimester screening of Down Syndrome (DS) and other pregnancy outcomes such as preeclampsia. For this purpose, we constructed an antibody array for indirect ("sandwich") measurement of seven serum proteins: pregnancy-associated plasma protein-A (PAPP-A), free beta subunit of human chorionic gonadotropin (fß-hCG), alpha-fetoprotein (AFP), angiopoietin-like 3 (ANGPTL3), epidermal growth factor (EGF), insulin-like growth factor 2 (IGFII), and superoxide dismutase 1 (SOD1). This array was tested using 170 DS cases and 510 matched controls drawn during the 8th-13th weeks of pregnancy. Data were used for prediction modelling and compared to previously obtained AutoDELFIA immunoassay data for PAPP-A and fß-hCG. PAPP-A and fß-hCG serum concentrations obtained using antibody arrays were highly correlated with AutoDELFIA data. Moreover, DS prediction modeling using (log-MoMmed) antibody array and AutoDELFIA data gave comparable results. Of the other markers, AFP and IGFII showed significant changes in concentration, although adding these markers to a prediction model based on prior risk, PAPP-A and fß-hCG did not improve the predictive performance. We conclude that implementation of antibody arrays in a prenatal screening setting is feasible but will require additional first trimester screening markers.

Biomarkers for circadian rhythm disruption independent of time of day.

Frequent shift work causes disruption of the circadian rhythm and might on the long-term result in increased health risk. Current biomarkers evaluating the presence of circadian rhythm disturbance (CRD), including melatonin, cortisol and body temperature, require 24-hr ("around the clock") measurements, which is tedious. Therefore, these markers are not eligible to be used in large-scale (human) studies. The aim of the present study was to identify universal biomarkers for CRD independent of time of day using a transcriptomics approach. Female FVB mice were exposed to six shifts in a clockwise (CW) and counterclockwise (CCW) CRD protocol and sacrificed at baseline and after 1 shift, 6 shifts, 5 days recovery and 14 days recovery, respectively. At six time-points during the day, livers were collected for mRNA microarray analysis. Using a classification approach, we identified a set of biomarkers able to classify samples into either CRD or non-disrupted based on the hepatic gene expression. Furthermore, we identified differentially expressed genes 14 days after the last shift compared to baseline for both CRD protocols. Non-circadian genes differentially expressed upon both CW and CCW protocol were considered useful, universal markers for CRD. One candidate marker i.e. CD36 was evaluated in serum samples of the CRD animals versus controls. These biomarkers might be useful to measure CRD and can be used later on for monitoring the effectiveness of intervention strategies aiming to prevent or minimize chronic adverse health effects.

Rodent models to study the metabolic effects of shiftwork in humans.

Our current 24-h society requires an increasing number of employees to work nightshifts with millions of people worldwide working during the evening or night. Clear associations have been found between shiftwork and the risk to develop metabolic health problems, such as obesity. An increasing number of studies suggest that the underlying mechanism includes disruption of the rhythmically organized body physiology. Normally, daily 24-h rhythms in physiological processes are controlled by the central clock in the brain in close collaboration with peripheral clocks present throughout the body. Working schedules of shiftworkers greatly interfere with these normal daily rhythms by exposing the individual to contrasting inputs, i.e., at the one hand (dim)light exposure at night, nightly activity and eating and at the other hand daytime sleep and reduced light exposure. Several different animal models are being used to mimic shiftwork and study the mechanism responsible for the observed correlation between shiftwork and metabolic diseases. In this review we aim to provide an overview of the available animal studies with a focus on the four most relevant models that are being used to mimic human shiftwork: altered timing of (1) food intake, (2) activity, (3) sleep, or (4) light exposure. For all studies we scored whether and how relevant metabolic parameters, such as bodyweight, adiposity and plasma glucose were affected by the manipulation. In the discussion, we focus on differences between shiftwork models and animal species (i.e., rat and mouse). In addition, we comment on the complexity of shiftwork as an exposure and the subsequent difficulties when using animal models to investigate this condition. In view of the added value of animal models over human cohorts to study the effects and mechanisms of shiftwork, we conclude with recommendations to improve future research protocols to study the causality between shiftwork and metabolic health problems using animal models.

Relationship of night and shift work with weight change and lifestyle behaviors.

OBJECTIVE: To prospectively study the association of night and shift work with weight change and lifestyle behaviors. METHODS: Workers participating in the Netherlands Working Conditions Cohort Study (2008 and 2009) (N = 5951) reported night and shift work, weight and height. Groups included stable night or shift work, from day work to night or shift work, from night or shift work to day work, and no night or shift work in 2008 and 2009. Regression analyses were used to study association changes in night and shift work with weight change and changes in lifestyle behaviors. RESULTS: A larger weight change was seen in normal-weight workers changing from day to shift work (ß = 0.93%; 95% confidence interval, 0.01 to 1.85) compared with stable no shift workers. No further associations of night and shift work with weight change were observed, neither in normal-weight, overweight, and obese workers. CONCLUSIONS: Despite the fact that starting night or shift work is associated with some unhealthy lifestyle habits, this study did not confirm a positive association of night and shift work with weight change over 1 year, except for normal-weight workers moving from day to shift work.

A day and night difference in the response of the hepatic transcriptome to cyclophosphamide treatment.

Application of omics-based technologies is a widely used approach in research aiming to improve testing strategies for human health risk assessment. In most of these studies, however, temporal variations in gene expression caused by the circadian clock are a commonly neglected pitfall. In the present study, we investigated the impact of the circadian clock on the response of the hepatic transcriptome after exposure of mice to the chemotherapeutic agent cyclophosphamide (CP). Analysis of the data without considering clock progression revealed common responses in terms of regulated pathways between light and dark phase exposure, including DNA damage, oxidative stress, and a general immune response. The overall response, however, was stronger in mice exposed during the day. Use of time-matched controls, thereby eliminating non-CP-responsive circadian clock-controlled genes, showed that this difference in response was actually even more pronounced: CP-related responses were only identified in mice exposed during the day. Only minor differences were found in acute toxicity pathways, namely lymphocyte counts and kidney weights, indicating that gene expression is subject to time of day effects. This study is the first to highlight the impact of the circadian clock on the identification of toxic responses by omics approaches.

Comparison of different blood collection, sample matrix, and immunoassay methods in a prenatal screening setting.

We compared how measurements of pregnancy-associated plasma protein A (PAPP-A) and the free beta subunit of human chorionic gonadotropin (fß-hCG) in maternal blood are influenced by different methods for blood collection, sample matrix, and immunoassay platform. Serum and dried blood spots (DBS) were obtained by venipuncture and by finger prick of 19 pregnant women. PAPP-A and fß-hCG from serum and from DBS were measured by conventional indirect immunoassay on an AutoDELFIA platform and by antibody microarray. We compared methods based on the recoveries for both markers as well as marker levels correlations across samples. All method comparisons showed high correlations for both marker concentrations. Recovery levels of PAPP-A from DBS were 30% lower, while those of fß-hCG from DBS were 50% higher compared to conventional venipuncture serum. The recoveries were not affected by blood collection or immunoassay method. The high correlation coefficients for both markers indicate that DBS from finger prick can be used reliably in a prenatal screening setting, as a less costly and minimally invasive alternative for venipuncture serum, with great logistical advantages. Additionally, the use of antibody arrays will allow for extending the number of first trimester screening markers on maternal and fetal health.

A range finding protocol to support design for transcriptomics experimentation: examples of in-vitro and in-vivo murine UV exposure.

In transcriptomics research, design for experimentation by carefully considering biological, technological, practical and statistical aspects is very important, because the experimental design space is essentially limitless. Usually, the ranges of variable biological parameters of the design space are based on common practices and in turn on phenotypic endpoints. However, specific sub-cellular processes might only be partially reflected by phenotypic endpoints or outside the associated parameter range. Here, we provide a generic protocol for range finding in design for transcriptomics experimentation based on small-scale gene-expression experiments to help in the search for the right location in the design space by analyzing the activity of already known genes of relevant molecular mechanisms. Two examples illustrate the applicability: in-vitro UV-C exposure of mouse embryonic fibroblasts and in-vivo UV-B exposure of mouse skin. Our pragmatic approach is based on: framing a specific biological question and associated gene-set, performing a wide-ranged experiment without replication, eliminating potentially non-relevant genes, and determining the experimental 'sweet spot' by gene-set enrichment plus dose-response correlation analysis. Examination of many cellular processes that are related to UV response, such as DNA repair and cell-cycle arrest, revealed that basically each cellular (sub-) process is active at its own specific spot(s) in the experimental design space. Hence, the use of range finding, based on an affordable protocol like this, enables researchers to conveniently identify the 'sweet spot' for their cellular process of interest in an experimental design space and might have far-reaching implications for experimental standardization.

Identification of interleukin-1 beta, but no other inflammatory proteins, as an early onset pre-eclampsia biomarker in first trimester serum by bead-based multiplexed immunoassays.

OBJECTIVE: This study aimed to determine the predictive value of growth factors, cardiovascular, and immunological markers for first trimester identification of early onset pre-eclampsia (PE). METHODS: In a retrospective case-control study, maternal serum samples of 35 early onset PE cases and 35 controls were analysed by multiplexed immunoassays, to determine serum concentrations of 41 proteins whose functionality can be associated with PE pathogenesis. All levels were converted into multiples of the gestation-specific normal median. For prediction modelling, proteins that were found to be significant were combined with previously obtained values of three established PE markers, that is, placental growth factor, placental protein 13, and pregnancy-associated plasma protein A. Prediction modelling was used to determine predicted detection rates for 5% and 10% false-positive rates. RESULTS: Three of the proteins examined in this study, interleukin-1 beta (IL-1ß), fibrinogen, and carcinoembryonic antigen, showed significantly different serum levels at p < 0.05. In prediction modelling, only IL-1ß added predictive value to the three previously established biomarkers, by increasing detection from 38.2% to 44.1% at a 5% false-positive rate. CONCLUSIONS: This study indicates that IL-1ß has potential to improve first trimester prediction of pre-eclampsia. Studies on larger cohorts will be needed to validate these findings.

A bead-based multiplexed immunoassay to evaluate breast cancer biomarkers for early detection in pre-diagnostic serum.

This study investigates whether a set of ten potential breast cancer serum biomarkers and cancer antigens (osteopontin (OPN), haptoglobin, cancer antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125), prolactin, cancer antigen 19-9 (CA19-9), α-fetoprotein (AFP), leptin and migration inhibitory factor (MIF)) can predict early stage breast cancer in samples collected before clinical diagnosis (phase III samples). We performed a nested case-control study within the Prospect-EPIC (European Prospective Investigation into Cancer and nutrition) cohort. We examined to what extent the biomarker panel could discriminate between 68 women diagnosed with breast cancer up to three years after enrollment and 68 matched healthy controls (all 56-64 years at baseline). Using a quantitative bead-based multiplexed assay, we determined protein concentrations in serum samples collected at enrollment. Principal Component Analysis (PCA) and Random Forest (RF) analysis revealed that on the basis of all ten proteins, early cases could not be separated from controls. When we combined serum protein concentrations and subject characteristics related to breast cancer risk in the RF analysis, this did not result in classification accuracy scores that could correctly classify the samples (sensitivity: 50%, specificity: 50%). Our findings indicate that this panel of selected tumor markers cannot be used for diagnosis of early breast cancer.

Biomarker discovery using a comparative omics approach in a mouse model developing heterogeneous mammary cancer subtypes.

Identification of biomarkers for early breast cancer detection in blood is a challenging task, since breast cancer is a heterogeneous disease with a wide range of tumor subtypes. This is envisioned to result in differences in serum protein levels. The p53(R270H/+) WAPCre mouse model is unique in that these mice spontaneously develop both ER- and ER+ tumors, in proportions comparable to humans. Therefore, these mice provide a well-suited model system to identify human relevant biomarkers for early breast cancer detection that are additionally specific for different tumor subtypes. Mammary gland tumors were obtained from p53(R270H/+) WAPCre mice and cellular origin, ER, and HER2 status were characterized. We compared gene expression profiles for tumors with different characteristics versus control tissue, and determined genes differentially expressed across tumor subtypes. By using literature data (Gene Ontology, UniProt, and Human Plasma Proteome), we further identified protein candidate biomarkers for blood-based detection of breast cancer. Functional overrepresentation analysis (using Gene Ontology, MSigDB, BioGPS, Cancer GeneSigDB, and proteomics literature data) showed enrichment for several processes relevant for human breast cancer. Finally, Human Protein Atlas data were used to obtain a prioritized list of 16 potential biomarkers that should facilitate further studies on blood-based breast cancer detection in humans.