BackgroundPlacental protein expression plays a crucial role during pregnancy. We hypothesized that:(1) circulating levels of pregnancy-associated, placenta-related proteins throughout gestation reflect the temporal progression of the uncomplicated, full-term pregnancy, and can effectively estimate gestational ages (GAs); and (2) preeclampsia (PE) is associated with disruptions in these protein levels early in gestation; and can identify impending PE. We also compared gestational profiles of proteins in the human and mouse, using pregnant heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like symptoms. MethodsSerum levels of placenta-related proteins-leptin (LEP), chorionic somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)-were quantified by ELISA in blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 20 subjects who developed PE with 61 samples). Multivariate analysis was performed to estimate the GA in PLOS ONEPLOS ONE | https://doi.org/10.The funders had no role in study design, data collection and analysis, normal pregnancy. Mean-squared errors of GA estimations were used to identify impending PE. The human protein profiles were then compared with those in the pregnant HO-1 Het mice. ResultsAn elastic net-based gestational dating model was developed (R 2 = 0.76) and validated (R 2 = 0.61) using serum levels of the 6 proteins measured at various GAs from women with normal uncomplicated pregnancies. In women who developed PE, the model was not (R 2 = -0.17) associated with GA. Deviations from the model estimations were observed in women who developed PE (P = 0.01). The model developed with 5 proteins (ELA excluded) performed similarly from sera from normal human (R 2 = 0.68) and WT mouse (R 2 = 0.85) pregnancies. Disruptions of this model were observed in both human PE-associated (R 2 = 0.27) and mouse HO-1 Het (R 2 = 0.30) pregnancies. LEP outperformed sFlt-1 and PlGF in differentiating impending PE at early human and late mouse GAs. ConclusionsSerum placenta-related protein profiles are temporally regulated throughout normal pregnancies and significantly disrupted in women who develop PE. LEP changes earlier than the well-established biomarkers (sFlt-1 and PlGF). There may be evidence of a causative action of HO-1 deficiency in LEP upregulation in a PE-like murine model. PLOS ONEMaternal serum biomarkers are associated with preeclampsia PLOS ONE | https://doi.org/10.

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ObjectiveThis study aimed to develop a blood test for the prediction of pre-eclampsia (PE) early in gestation. We hypothesised that the longitudinal measurements of circulating adipokines and sphingolipids in maternal serum over the course of pregnancy could identify novel prognostic biomarkers that are predictive of impending event of PE early in gestation.Study designRetrospective discovery and longitudinal confirmation.SettingMaternity units from two US hospitals.ParticipantsSix previously published studies of placental tissue (78 PE and 95 non-PE) were compiled for genomic discovery, maternal sera from 15 women (7 non-PE and 8 PE) enrolled at ProMedDx were used for sphingolipidomic discovery, and maternal sera from 40 women (20 non-PE and 20 PE) enrolled at Stanford University were used for longitudinal observation.Outcome measuresBiomarker candidates from discovery were longitudinally confirmed and compared in parallel to the ratio of placental growth factor (PlGF) and soluble fms-like tyrosine kinase (sFlt-1) using the same cohort. The datasets were generated by enzyme-linked immunosorbent and liquid chromatography-tandem mass spectrometric assays.ResultsOur discovery integrating genomic and sphingolipidomic analysis identified leptin (Lep) and ceramide (Cer) (d18:1/25:0) as novel biomarkers for early gestational assessment of PE. Our longitudinal observation revealed a marked elevation of Lep/Cer (d18:1/25:0) ratio in maternal serum at a median of 23 weeks’ gestation among women with impending PE as compared with women with uncomplicated pregnancy. The Lep/Cer (d18:1/25:0) ratio significantly outperformed the established sFlt-1/PlGF ratio in predicting impending event of PE with superior sensitivity (85% vs 20%) and area under curve (0.92 vs 0.52) from 5 to 25 weeks of gestation.ConclusionsOur study demonstrated the longitudinal measurement of maternal Lep/Cer (d18:1/25:0) ratio allows the non-invasive assessment of PE to identify pregnancy at high risk in early gestation, outperforming the established sFlt-1/PlGF ratio test.

ObjectivesThe aim of this study was to develop a single blood test that could determine gestational age and estimate the risk of preterm birth by measuring serum metabolites. We hypothesised that serial metabolic modelling of serum analytes throughout pregnancy could be used to describe fetal gestational age and project preterm birth with a high degree of precision.Study designA retrospective cohort study.SettingTwo medical centres from the USA.ParticipantsThirty-six patients (20 full-term, 16 preterm) enrolled at Stanford University were used to develop gestational age and preterm birth risk algorithms, 22 patients (9 full-term, 13 preterm) enrolled at the University of Alabama were used to validate the algorithms.Outcome measuresMaternal blood was collected serially throughout pregnancy. Metabolic datasets were generated using mass spectrometry.ResultsA model to determine gestational age was developed (R2=0.98) and validated (R2=0.81). 66.7% of the estimates fell within ±1 week of ultrasound results during model validation. Significant disruptions from full-term pregnancy metabolic patterns were observed in preterm pregnancies (R2=−0.68). A separate algorithm to predict preterm birth was developed using a set of 10 metabolic pathways that resulted in an area under the curve of 0.96 and 0.92, a sensitivity of 0.88 and 0.86, and a specificity of 0.96 and 0.92 during development and validation testing, respectively.ConclusionsIn this study, metabolic profiling was used to develop and test a model for determining gestational age during full-term pregnancy progression, and to determine risk of preterm birth. With additional patient validation studies, these algorithms may be used to identify at-risk pregnancies prompting alterations in clinical care, and to gain biological insights into the pathophysiology of preterm birth. Metabolic pathway-based pregnancy modelling is a novel modality for investigation and clinical application development.

1Background: Placental protein expression plays a crucial biological role during normal and 2 complicated pregnancies. We hypothesized that: (1) circulating pregnancy-associated, placenta-3 related protein levels throughout gestation reflect the uncomplicated, full-term temporal 4 progression of human gestation, and effectively estimates gestational ages (GAs); (2) 5 pregnancies with underlying placental pathology, such as preeclampsia (PE), are associated with 6 disruptions in this GA estimation in early gestation; (3) malfunctions of this GA estimation can 7 be employed to identify impending PE. In addition, to explore the underlying biology and PE 8 etiology, we set to compare protein gestational patterns of human and mouse, using pregnant 9 heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like 10 symptoms. 11Methods: Serum levels of circulating placenta-related proteins -leptin (LEP), chorionic 12 somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like 13 tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)-were quantified by ELISA in 14 blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 15 20 PE subjects with 61 samples). Linear multivariate analysis of the targeted serological protein 16 levels was performed to estimate the normal GA. Logarithmic transformed mean-squared errors 17 of GA estimations were used to identify impending PE. Then the human gestational protein 18 patterns were compared to those in the pregnant HO-1 mice. 19Results: An elastic net (EN)-based gestational dating model was developed (R 2 = 0.76) and 20 validated (R 2 = 0.61) using the serum levels of the 6 proteins at various GAs from women with 21 normal uncomplicated pregnancies (n = 10 for training and n = 6 for validation). In pregnancies 22 complicated by PE (n = 14), the EN model was not (R 2 = -0.17) associated with GA at sampling 23 3 3 in PE. Statistically significant deviations from the normal GA EN model estimations were 24 observed in PE-associated pregnancies between GAs of 16-30 weeks (P = 0.01). The EN model 25 developed with 5 proteins (ELA excluded due to the lack of robustness of the mouse ELA essay) 26 performed similarly on normal human (R 2 = 0.68) and WT mouse (R 2 = 0.85) pregnancies. 27 Disruptions of this model were observed in both human PE-associated (human: R 2 = 0.27) and 28 mouse HO-1 Het (mouse: R 2 = 0.30) pregnancies. LEP out performed sFlt-1 and PlGF in 29 differentiating impending PE at early human and late mouse gestations. 30 Conclusions: As revealed in both human and mouse GA EN analyses, temporal serological 31 placenta-related protein patterns are tightly regulated throughout normal human pregnancies and 32 can be significantly disrupted in pathologic PE states. LEP changes earlier during gestation than 33 the well-established late GA PE biomarkers (sFlt-1 and PlGF). Our HO-1 Het mouse analysis 34 provides direct evidence of the causative action of HO-1 deficiency in LEP upregulation in a...

Ceramides and dihydroceramides are sphingolipids that present in abundance at the cellular membrane of eukaryotes.Although their metabolic dysregulation has been implicated in many diseases, our knowledge about circulating ceramide changes during the pregnancy remains limited. In this study, we present the development and validation of a highthroughput liquid chromatography-tandem mass spectrometric (LC/MS/MS) method for simultaneous quantification of 16 ceramides and 10 dihydroceramides in human serum within 5 mins by using stable isotope-labeled ceramides as internal standards (ISs). This method employs a protein precipitation method for high throughput sample preparation, reverse phase isocratic elusion for chromatographic separation, and Multiple Reaction Monitoring (MRM) for mass spectrometric detection. To qualify for clinical applications, our assay was validated against the FDA guidelines: the Lower Limit of Quantitation (LLOQ as low as 1 nM), linearity (R 2 >0.99), precision (Coefficient of Variation<15%), accuracy (Percent Error<15%), extraction recovery (>90%), stability (>85%), and carryover (<0.1%). With enhanced sensitivity and specificity from this method, we have, for the first time, determined the serological levels of ceramides and dihydroceramides to reveal unique temporal gestational patterns. Our approach could have value in providing insights into disorders of pregnancy.

244 Background: Implementation of population screening for colorectal cancer (CRC) before colonoscopy can reduce the challenge of the overall capacity of bowel examination and improve survival. Blood based CRC assessment biomarkers, on a triage concept, can lead to improved selection to colonoscopy and cost-effective CRC care. Methods: Innovative multi-omics approaches, with global and targeted LCMS data production (metabolomics, lipidomics, and 2D proteomics) and integrative data analytics, were applied to discover serological biomarkers to assess nonadvanced adenoma and identify stage I/II colorectal bowel lesions. A cohort of 2396 normal, 660 adenoma, 953 stage I, and 101 stage II blood samples, was constructed to discover screening biomarkers to support case finding of patients at high risk for nonadvanced adenoma and stage I/II cancer for subsequent diagnostic colonoscopy. Results: A three-analyte mProbe panel was constructed which outperformed the commercial assays of plasma methylated septin 9 and fecal Cologuard tests. Sensitivity: (1) nonadvanced adenoma–Cologuard 17.2%, mProbe 76.0%; (2) stage I-III-Cologuard 93.3%, stage I-II Septin 9 (ARUP laboratories) 77%, stage I-II mProbe: 92.3%. Specificity–Cologuard 89.8%, Septin 9 (ARUP laboratories) 88%, mProbe 90.7%. Conclusions: mProbe triage concept of a blood-based protein biomarker panel promises the precision to allow future CRC screening, and reduce the low-risk utilization of unnecessary, unpleasant and risk-associated bowel examinations.

3613 Background: One-third of colorectal cancer (CRC) recurs following curative surgery and chemotherapy. Accordingly, novel methods are needed to predict recurrence to enable clinical course mitigating strategies. Serial monitoring of plasma by mass spectrometry (MS) and multi-omics modeling (MMO) of CRC relapse chronology provide the framework for liquid biopsy test development to supersede existing imaging modalities such as CT scans according to relapse related pathologies. We hypothesized that plasma MS and MMO analysis of relapse related pathologies can deconvolute high risk stratification for CRC recurrence within the cancer continuum of care pre/post-surgery and/or pre/post adjuvant chemotherapy (ACT). Methods: 189 CRC patients (Stage I-III) underwent one of three treatment modalities: Modality 1 (Surgery followed by ACT), Modality 2 (Surgery only), Modality 3 (Neoadjuvant chemotherapy followed by surgery and ACT). Plasma samples (n = 441) were collected from patients before surgery, 30 days post-op, and every 3 months until death or month 24 whichever came first. The MMO approach was used to analyze biological features encompassing native peptides, proteins, metabolites, lipids, and ceramides. MMO panels were developed comprising the significantly perturbed features as per the treatment modalities. These panels were used to predict relapse from plasma collected pre-op, 30-day post-op or after adjuvant chemotherapy. CEA levels were monitored in parallel. Results: Follow-up data was available for 135 patients (Stage I-III) and 25/135 had evidence of radiological recurrence. Irrespective of the treatment modality, longitudinal follow-up using the MMO panel was able to predict disease recurrence greater than 7 months before clinical progression was confirmed by CT scan. There was no significant correlation between longitudinal CEA levels and recurrence status, hence CEA levels alone did not provide any lead time advantage over the MMO panel or radiological surveillance. Kaplan-Meier (KM) survival analysis revealed that patients that were MMO panel positive had a poor survival irrespective of treatment modalities used: Modality 1 (HR = 6.2, p value = 0.003, test immediately post-surgery and immediately before ACT; HR = 31.6, p value = 0.01, test immediately after ACT); Modality 2 (HR = 11.2; p value = 0.01, test immediately after-surgery); Modality 3 (HR > 40, p value = 0.08, test immediately after neo-ACT and before-surgery; HR > 40, p value = 0.004, test immediately after-surgery). Conclusions: The MMO panel predicts CRC recurrence several months prior to detection by conventional CT scans, thus providing opportunity for alternative therapeutic strategies much earlier in the disease course.