Diagnostic Biomarkers for Predicting Adverse Early Pregnancy Outcomes

Maternal Morbidity Risk Factors in Nulliparas

OBJECTIVE

 For every incidence of maternal mortality, maternal morbidity is thought to occur in another 50 to 100 individuals in the United States. Multiple risk factors for severe maternal morbidity have been identified, but counseling about specific risk in pregnancy remains difficult, particularly nulliparous individuals as prior obstetric history is one of the factors influencing risk for severe maternal morbidity. The objective of this study is to examine the association between sociodemographic and laboratory assessments in the first trimester and maternal morbidity in nulliparas.

STUDY DESIGN

 This was a secondary analysis of a large, multicenter prospective observational cohort of nulliparas. The primary maternal outcome was a composite of hypertensive disorders of pregnancy (HDP), hemorrhage (transfusion, hemorrhage, hysterectomy, other surgery, readmission for bleeding), infection (endometritis, wound infection or dehiscence, pneumonia, sepsis, infection during labor and delivery, readmission for infection through day 14), venous thromboembolic events (VTE) (deep venous thrombosis, or pulmonary embolus), or maternal death within 14 days of delivery. Sociodemographic and clinical factors were compared between people with and without maternal morbidity. Relative risk and 95% confidence interval for maternal morbidity was calculated using log-binomial regression, adjusted for baseline characteristics that had a significant independent relationship with maternal morbidity with a p-value <0.05.

RESULTS

 Of 9,445 pregnant people in the analysis, 18.2% (n = 1,716) experienced the composite maternal morbidity; the most common component was HDP (13.1%, n = 1,244) followed by infection (4.43%, n = 420), hemorrhage (2.27%, n = 215), VTE (0.12%, n = 11), and death (0.01%, n = 1). In a multivariable model, self-identified Black race, first trimester obesity, pregestational diabetes, chronic hypertension, and chronic kidney disease were significantly associated with the primary maternal outcome.

CONCLUSION

 More than one in six nulliparas experienced the composite maternal morbidities. Maternal morbidity was associated with self-identified Black race, obesity, and multiple preexisting medical comorbidities.

KEY POINTS

· One in six nulliparas experience maternal morbidity in their first pregnancy related to hypertensive disorders of pregnancy, infection, hemorrhage, and venous thromboembolism.. · Risk factors for maternal morbidity in nulliparas include Black race, prepregnancy body mass index, and preexisting medical conditions.. · The preexisting medical conditions with the strongest association with maternal morbidity included pregestational diabetes, chronic hypertension, and chronic kidney disease..

Kisspeptin as a predictor of miscarriage: a systematic review

OBJECTIVE

A highly accurate serum marker for predicting viable pregnancy needs to be developed. Recent studies have demonstrated that kisspeptin is a potential biomarker for this purpose.

METHODS

This systematic review evaluated the available data in the literature on the role of kisspeptin as a miscarriage biomarker. A literature search was conducted in the PubMed/Medline, Embase, Web of Science, and Scopus databases using the following keywords: (kisspeptin) AND (miscarriage OR pregnancy loss OR spontaneous abortion OR reproductive failure).

RESULTS

Seven case-control studies were selected for the systematic review. The included papers described the potential role of kisspeptin as a putative biomarker of pregnancy loss. Furthermore, two studies reported that changes in kisspeptin levels may be associated with unexplained infertility and low rates of embryo implantation in women undergoing assisted reproductive technology.

CONCLUSION

Kisspeptin might be used as a potential biomarker of pregnancy viability in the near future. However, studies with better evidence are needed to establish the applicability of kisspeptin as a diagnostic and prognostic tool.

Identification of technology frontiers of artificial intelligence-assisted pathology based on patent citation network

Objectives

This paper aimed to identify the technology frontiers of artificial intelligence-assisted pathology based on patent citation network.

Methods

Patents related to artificial intelligence-assisted pathology were searched and collected from the Derwent Innovation Index (DII), which were imported into Derwent Data Analyzer (DDA, Clarivate Derwent, New York, NY, USA) for authority control, and imported into the freely available computer program Ucinet 6 for drawing the patent citation network. The patent citation network according to the citation relationship could describe the technology development context in the field of artificial intelligence-assisted pathology. The patent citations were extracted from the collected patent data, selected highly cited patents to form a co-occurrence matrix, and built a patent citation network based on the co-occurrence matrix in each period. Text clustering is an unsupervised learning method, an important method in text mining, where similar documents are grouped into clusters. The similarity between documents are determined by calculating the distance between them, and the two documents with the closest distance are combined. The method of text clustering was used to identify the technology frontiers based on the patent citation network, which was according to co-word analysis of the title and abstract of the patents in this field.

Results

1704 patents were obtained in the field of artificial intelligence-assisted pathology, which had been currently undergoing three stages, namely the budding period (1992–2000), the development period (2001–2015), and the rapid growth period (2016–2021). There were two technology frontiers in the budding period (1992–2000), namely systems and methods for image data processing in computerized tomography (CT), and immunohistochemistry (IHC), five technology frontiers in the development period (2001–2015), namely spectral analysis methods of biomacromolecules, pathological information system, diagnostic biomarkers, molecular pathology diagnosis, and pathological diagnosis antibody, and six technology frontiers in the rapid growth period (2016–2021), namely digital pathology (DP), deep learning (DL) algorithms—convolutional neural networks (CNN), disease prediction models, computational pathology, pathological image analysis method, and intelligent pathological system.

Conclusions

Artificial intelligence-assisted pathology was currently in a rapid development period, and computational pathology, DL and other technologies in this period all involved the study of algorithms. Future research hotspots in this field would focus on algorithm improvement and intelligent diagnosis in order to realize the precise diagnosis. The results of this study presented an overview of the characteristics of research status and development trends in the field of artificial intelligence-assisted pathology, which could help readers broaden innovative ideas and discover new technological opportunities, and also served as important indicators for government policymaking.

A new method for broadening the detection range of immunoassay and its application in β-hCG quantitative detection

Early pregnancy prediction requires very high β-hCG detection sensitivity, while embryonic development monitoring and trophoblastic disease detection require a wider detection range. In this study, based on light-initiated chemiluminescence assay (LICA), one high-affinity mAb and one low-affinity mAb were selected and coated on chemibeads with a larger coating area in different ratios to immobilize the antibodies. The two immobilized mAbs were mixed with different concentrations to detect β-hCG. When the high-affinity mAb-coated chemibeads and low-affinity mAb-coated chemibeads were used at working concentrations of 0.100 mg mL^-1 and 0.014 mg mL^-1, respectively, the sensitivity and detection range were maximized. The assay was precise for measuring β-hCG with repeatability and intermediate precision of <5% CV. The assay has a high sensitivity with a limit of quantification (LoQ) of 0.49 IU L^-1, which is lower than that of most β-hCG detection kits. Over the range of 1 IU L^-1 to 16 000 IU L^-1, the assay had a proper linearity (r = 0.9995). No false negative results due to the hook effect were observed at β-hCG concentrations up to 225 000 IU L^-1. The assay showed a good correlation with the Abbott assay (r = 0.9910). LICA combined with immobilized mAbs with different affinities ensures the sensitivity of β-hCG detection and broadens the detection range.

Performance of plasma kisspeptin as a biomarker for miscarriage improves with gestational age during the first trimester

OBJECTIVE

To compare the performance of kisspeptin and beta human chorionic gonadotropin (βhCG), both alone and in combination, as biomarkers for miscarriage throughout the first trimester.

DESIGN

Prospective, nested case-control study.

SETTING

Tertiary Centre, Queen Charlotte Hospital, London, United Kingdom.

PATIENT(S)

Adult women who had miscarriages (n = 95, 173 samples) and women with healthy pregnancies (n = 265, 557 samples).

INTERVENTION(S)

The participants underwent serial ultrasound scans and blood sampling for measurement of plasma kisspeptin and βhCG levels during the first trimester.

MAIN OUTCOME MEASURE(S)

The ability of plasma kisspeptin and βhCG levels to distinguish pregnancies complicated by miscarriage from healthy pregnancies unaffected by miscarriage.

RESULT(S)

Gestation-adjusted levels of circulating kisspeptin and βhCG were lower in samples from women with miscarriages than in women with healthy pregnancies by 79% and 70%, respectively. The area under the receiver-operating characteristic curve for identifying miscarriage during the first trimester was 0.874 (95% confidence interval [CI] 0.844-0.904) for kisspeptin, 0.859 (95% CI 0.820-0.899) for βhCG, and 0.916 (95% CI 0.886-0.946) for the sum of the two markers. The performance of kisspeptin in identifying miscarriage improved with increasing length of gestation, whereas that of βhCG worsened. A decision matrix incorporating kisspeptin, βhCG, and gestational age had 83% to 87% accuracy for the prediction of miscarriage.

CONCLUSION(S)

Plasma kisspeptin is a promising biomarker for miscarriage and provides additional value to βhCG alone, especially during later gestational weeks of the first trimester.

Thrombophilia, Inflammation, and Recurrent Pregnancy Loss: A Case-Based Review

Recurrent pregnancy loss (RPL) is defined as the loss of two or more pregnancies and is often multifactorial with the majority of miscarriages being due to aneuploidy and anatomic or physiological abnormalities. However, inherited or acquired thrombophilias have also been associated with RPL, albeit inconsistently. While inherited thrombophilias, such as factor V Leiden and prothrombin gene mutation, are relatively prevalent in women with RPL compared with the general population, a causal link has yet to be definitively established. Recently, systemic inflammation, as measured by high-sensitivity C-reactive protein, has also been hypothesized to play a role in infertility. Based on limited prospective trial data, antithrombotic therapy and antiplatelet agents have been proposed as possible tools for the prevention of RPL. Because of the multifactorial nature of RPL and infertility, various clinicians, as obstetricians and gynecologists, endocrinologists, hematologists, or vascular medicine specialists, may be requested to counsel these women. This, together with evidence gaps, frequently leads to distinctly different diagnostic and therapeutic recommendations, especially regarding thrombophilia testing and treatment. Using four case vignettes in this review, we critically appraise the literature and highlight how two clinicians from different subspecialties approach the relationship between RPL, inflammation, and thrombophilia.

Biochemical and hematological biomarkers of reproductive failure in bottlenose dolphins Tursiops truncatus

The physiological demands of pregnancy inevitably result in alterations in both biochemical and hematological parameters as fetal development occurs. The shifts observed in successful pregnancy in bottlenose dolphins Tursiops truncatus to support both fetal physiological needs and maternal basal requirements have been established according to each trimester. Detecting aberrations in blood-based biomarkers could help facilitate diagnosis of gestational abnormalities, improve our understanding of factors influencing reproductive outcomes and aid in prediction of reproductive failure. This study retrospectively analyzed 263 blood samples from 15 bottlenose dolphins in 21 failed pregnancies over 28 yr (1989-2017). Most samples remained within normal pregnancy reference ranges; however, significant shifts were observed between trimesters. Hematological alterations, compared to successful pregnancy reference ranges from previously published data, were consistent across failed pregnancies and included an increased prevalence of elevated 2nd and 3rd trimester neutrophils, elevated 2nd trimester monocytes and decreased 3rd trimester eosinophils. In addition, low hematocrit and low red blood cells were more prevalent in the 2nd trimester. Biochemical shifts included an increased prevalence of elevated creatine phosphokinase in the 3rd trimester outside of the normal reference ranges. Across failed pregnancies, calcium and iron were decreased in the 3rd trimester. Significantly decreased progesterone in the 3rd trimester was a negative prognostic indicator of pregnancy outcome with decreasing 3rd trimester progesterone associated with failed pregnancy. This study demonstrates the use of blood-based biomarkers as possible predictors of pregnancy outcome in bottlenose dolphins.

Quantitative proteomics analysis identifies salivary biomarkers for early detection of pregnancy loss in a Singaporean cohort-A pilot study

PURPOSE

Early pregnancy loss (EPL) is one of the most common complications encountered in clinical practice. As most of EPLs occur relatively early on during pregnancy, they are often misunderstood as an expected menstrual cycle. Thus, it is essential to investigate the diagnostic biomarkers for monitoring pregnancy loss for continuous non-invasive monitoring of EPL.

EXPERIMENTAL DESIGN

Unstimulated saliva was collected from 10 subjects with EPL and a matched cohort of healthy pregnant women as controls. Samples were analyzed using iTRAQ analysis, and ELISA was performed to validate results.

RESULTS

Enrichment analysis of the 38 differentially abundant proteins identified that regulation of nucleobase, nucleoside, nucleotide, and nucleic acid metabolism was significantly affected in EPL. The nucleosome assembly pathway was significantly underrepresented in EPL and was associated with depletion of histone proteins (H2B, H3, and H4). These results were validated with ELISA experiments. A depletion of histones can impair nucleosome assembly and cause the nuclear machinery to fail.

CONCLUSION

Regulation of nucleosome is critical for the maintenance of genome stability and epigenetic information, lack of which may lead to pregnancy loss. Thus, assessing and monitoring salivary histone levels in patients with threatened miscarriage can be a quick and easy method of obtaining periodic diagnostic information that can speed up treatment decisions.

CLINICAL RELEVANCE

There is considerable uncertainty regarding the prognosis of threatened pregnancy, making it stressful for expecting mothers and healthcare professionals. Most EPLs are often misunderstood or ignored as an expected menstrual cycle. Thus it is essential to develop screenings and rapid detection devices using a medium that can be non-invasive and self-performed for continuous monitoring. Using saliva, we have identified that the nucleosome assembly gets affected in EPL with depletion of histone proteins (H2B, H3, and H4). With further verification, these findings can help saliva be utilized as a medium to determine which patients will/will not progress to miscarriage and at what point of their pregnancy. Assessing and monitoring EPL using salivary diagnostics can be a quick and easy method of obtaining periodic diagnostic information that can speed up treatment decisions. Hence, these findings need to be investigated further to improve the prediction of outcomes in women with threatened pregnancy.

First-Trimester Prognosis When an Early Gestational Sac is Seen on Ultrasound Imaging: Logistic Regression Prediction Model

OBJECTIVES

To determine the factors that jointly and independently affect first-trimester outcome of very early intrauterine pregnancies (those whose sonogram shows a gestational sac with no identifiable yolk sac or embryo) and develop a mathematical model and Web-based calculator that computes prognosis based on these factors.

METHODS

Our study population included 590 very early pregnancies scanned between January 1, 2012, and June 30, 2018, with known outcomes (live or spontaneous loss) at 14 weeks. We recorded patient age, mean sac diameter (MSD), human chorionic gonadotropin (hCG) rise, and presence/absence of: vaginal bleeding, history of infertility, prior miscarriage, and pregnancy via assisted reproductive technology. We assessed the correlation between each of these factors and outcome and performed stepwise logistic regression to determine the subset that independently correlated with outcome.

RESULTS

Patient age, MSD, hCG rise, vaginal bleeding, history of infertility, and assisted reproductive technology pregnancy were significantly correlated with outcome (P < .05, t test for age and MSD, χ² for the others). Stepwise logistic regression identified age, MSD, hCG rise, and vaginal bleeding as the subset of factors that independently predicted outcome. The regression model's area under the receiver operating characteristic curve was 0.823. We incorporated the regression model into a Web-based calculator (https://tinyurl.com/Prognosis-PD) that predicts the outcome of an early intrauterine pregnancy based on these 4 key variables.

CONCLUSIONS

The prognosis of very early intrauterine pregnancies is related to several clinical, biochemical, and sonographic factors. The factors that independently correlate with first-trimester outcome are patient age, MSD, hCG rise, and vaginal bleeding. The logistic regression model predicts outcome based on these variables.

Reproducibility of saliva progesterone measured by immunoassay compared to liquid chromatography mass spectrometry

Immunoassay overestimates progesterone in blood, but no studies have tested whether this occurs in saliva. We measured progesterone in saliva using immunoassay and mass spectrometry. We tested the immunoassay for cross reactivity with dehydroepiandrosterone sulfate (DHEA-S) and 17α-hydroxyprogesterone (17α-OHP). Progesterone was significantly higher in immunoassay compared to mass spectrometry. Immunoassay progesterone levels increased in when incremental levels of 17α-OHP standard was added. This effect was not observed with the addition of DHEA-S. Research using salivary progesterone immunoassay techniques should be wary, particularly with individuals taking steroid supplementation or with high levels of progesterone metabolites.

Hydrogel-Embedded Quantum Dot-Transcription Factor Sensors for Quantitative Progesterone Detection

Immobilization of biosensors in or on a functional material is critical for subsequent device development and translation to wearable technology. Here, we present the development and assessment of an immobilized quantum dot-transcription factor-nucleic acid complex for progesterone detection as a first step toward such device integration. The sensor, composed of a polyhistidine-tagged transcription factor linked to a quantum dot and a fluorophore-modified cognate DNA, is embedded within a hydrogel as an immobilization matrix. The hydrogel is optically transparent, soft, and flexible as well as traps the quantum dot-transcription factor DNA assembly but allows free passage of the analyte, progesterone. Upon progesterone exposure, DNA dissociates from the quantum dot-transcription factor DNA assembly resulting in an attenuated ratiometric fluorescence output via Förster resonance energy transfer. The sensor performs in a dose-dependent manner with a limit of detection of 55 nM. Repeated analyte measurements are similarly successful. Our approach combines a systematically characterized hydrogel as an immobilization matrix and a transcription factor-DNA assembly as a recognition/transduction element, offering a promising framework for future biosensor devices.

A risk model of prenatal screening markers in first trimester for predicting hypertensive disorders of pregnancy

Background

We aimed to construct a risk model to assess the diagnostic value of predicting hypertensive disorders of pregnancy (HDPs) by screening a range of prenatal markers, including pregnancy-associated plasma protein A (PAPP-A), free beta-human chorionic gonadotropin (free β-hCG), and fetal nuchal translucency (NT).

Method

We analyzed 902 women, classified into four groups: healthy gravidas (n = 680, controls), gravidas with gestational hypertension (n = 61; GH), gravidas with preeclampsia (n = 90; PE), and gravidas with severe preeclampsia (n = 71, SPE). We then compared the multiple of median (MoM) of PAPP-A, free β-hCG, and NT. A risk model was constructed and receiver operating characteristic curve (ROC) analysis was used to diagnose HDPs.

Results

Levels of PAPP-A and free β-hCG levels in the GH, PE, and SPE groups were significantly lower than those in the control group (χ ² = 7.522, P = 0.001; χ ² = 17.775, P < 0.001). NT did not differ significantly when compared across all four groups (χ ² = 1.592, P > 0.05). When the cut-off values for PAPP-A and free β-hCG were 0.795 MoM and 1.185 MoM, the corresponding sensitivities and specificities were 0.514 and 0.635, and 0.734 and 0.450, respectively. The best risk calculation featured PAPP-A, free β-hCG, and NT; this model exhibited the highest diagnostic value in the SPE group, followed by the GH group and then the PE group.

Conclusion

The use of prenatal screening markers during early pregnancy can identify fetal aneuploidy and can also predict HDPs. The development of innovative screening strategies for gravidas and the targeted prevention of HDPs in high-risk gravidas are essential for perinatal care and early intervention, thus creating significant opportunities for predictive and preventive personalized medicine. In our study, we found that the combination of a series of prenatal screening markers in early pregnancy is better than a single marker; our data clearly demonstrate the diagnostic value of combining PAPP-A, free β-hCG, and NT for patients with SPE.

Accurate detection of β-hCG in women's serum and cervical secretions for predicting early pregnancy viability based on time-resolved luminescent lanthanide nanoprobes

Sensitive and specific detection of β-hCG in women's serum and cervical secretions is of great significance for early pregnancy evaluation. However, the accurate detection of trace amounts of β-hCG in cervical secretions remains challenging because of its low level. Herein, we report a unique strategy for β-hCG detection in a heterogeneous sandwich-type bioassay by using LiLuF₄:Ce,Tb nanoparticles as time-resolved photoluminescence (PL) nanoprobes. By taking advantage of the intense and long-lived PL of the nanoprobes, the short-lived background autofluorescence can be completely eliminated, which enables the sensitive detection of β-hCG with a linear range of 0-10 ng mL^-1 and a detection limit down to 6.1 pg mL^-1, approximately two orders of magnitude improvement relative to that of a commercial β-hCG assay kit. Furthermore, we demonstrate the application of the nanoprobes for accurate detection of β-hCG in clinical serum and cervical secretion samples and unveil that the ratio of β-hCG levels in cervical secretions and serum can be a good indicator of early pregnancy viability in unknown locations. These findings bring new opportunities in perinatal medicine by employing luminescent lanthanide nanoprobes, thus laying a foundation for future development of luminescent nanoprobes for versatile biomedical applications.