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Can a New Blood Test Predict a Harmful Pregnancy Condition?

Placenta accreta spectrum (PAS) is a condition that results when the placenta grows deeper into the wall of the uterus than normal, essentially penetrating the wall of a woman’s uterus. PAS can lead to serious complications such as severe bleeding, hysterectomy, and potentially death. The incidence of PAS is increasing globally, but detection of it prior to birth is largely unsuccessful. If caught early and patients receive appropriate care, deaths during or after pregnancy (maternal mortality) could be reduced by up to 80%, so identifying PAS early or during the middle of a pregnancy is key to reducing maternal mortality and other related complications worldwide.

Currently, diagnosis of PAS is based on risk factors such as another condition called placenta previa and prior cesarean delivery. However, this approach to diagnosing PAS is not very accurate as it fails to detect PAS in up to half of the cases. Some other approach is needed. A readily accessible way to discovery PAS in the body (aka a “biomarker”) would be highly beneficial in terms of both diagnosis and understanding its mechanisms, especially in low-resource and rural settings without specialized medical equipment such as ultrasound services. A recent study focused on figuring out how to use a biomarker to detect PAS.

Logic Behind the Research

Researchers studied a biomarker known as circulating microparticles (CMPs). These are involved in communicating information between cells and triggering certain actions between cells. They have been studied in relation to cancer care and obstetrics, showing promise in helping understand preterm birth, preeclampsia, and PAS. This study aimed to find how components of CMPS could identify pregnancies complicated by PAS with the goal of identifying a clinically useful biomarker, as well as understanding more about the role of the biomarkers in the PAS disease process.

Who was involved in the study?

This study evaluated 35 PAS cases and 70 controls (people without the condition). Compared to controls, older maternal age and placenta previa at delivery were more likely in PAS cases. Twenty-three (65.7%) of the PAS cases were determined by clinicians using existing strategies. Some were determined by examining the a sample of the uterus following birth. Only a few of the early stage cases were detected using ultrasound (around 11%).

Results

The researchers demonstrated that a panel of five different proteins connected to CMPs in the second trimester and a panel of four proteins in the third trimester can both identify PAS. The degree of accuracy to which these proteins worked suggests that they may be useful for clinical practice. This finding offers insights into underlying mechanisms of the illness, as well as potential for earlier diagnosis and patient counseling. The proteins identified are associated with the cells moving into the uterus wall, creating new blood vessels, cell death, and also other factors that challenge the survival of cells. The proteins connected to the second trimester panel seem to be more predictive than the proteins associated with the third trimester due to changes in placental growth at this stage.

Results suggest that proteins in the second trimester panel are more specific to invasion of cells into the uterus wall and creation of new blood vessels than those in the third trimester. This is possibly due to changes in placental growth which may lead to increased CMP movement into uterus wall and a more predictive disease signal. Clinically, this timepoint corresponds with a routine blood draw for gestational diabetes and allows for earlier diagnosis, patient counseling, and multidisciplinary care.

Future Efforts

This study stands out from prior PAS biomarker studies for several reasons. Inclusion into the PAS disease group did not require prior PAS diagnosis or suspicion by ultrasound, 77% of PAS cases were not detected before birth, and it represents the entire spectrum of disease. A high-performing biomarker panel was detected with promising potential to improve pre-birth detection of even the most elusive PAS cases and ensure appropriate preparations can take place prior to delivery.

This is the first study to use CMP proteins for classifying PAS, advancing the mechanistic understanding of PAS and search for treatments, as well as identify pregnancies affected by PAS for improved maternal outcomes. Future studies are needed to independently replicate the findings of this study.

Perry Payne
Dr. Perry Payne is a public health practitioner and scholar with expertise in quality of care, health equity, prescription drug policy, and health care ethics. He has over ten years of experience as a freelance health care/medical writer and editor. His full-time work experience includes working as a professor and researcher in universities, serving as a federal government official, and a brief stint working for healthcare technology companies.

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