Plasma protein can predict perinatal mood and anxiety disorders


In a recent study, patients at risk of perinatal mood and anxiety disorders presented with different plasma protein levels than those not at risk.

Plasma protein can predict perinatal mood and anxiety disorders | Image Credit: © tadamichi - © tadamichi -

Plasma protein can predict perinatal mood and anxiety disorders | Image Credit: © tadamichi - © tadamichi -

According to a recent study published in the American Journal of Obstetrics & Gynecology, many perinatal mood and anxiety disorders (PMADs) have unique plasma protein signatures.

PMADs, including generalized anxiety disorder, major depressive disorder, panic disorder, obsessive compulsive disorder, and posttraumatic stress disorder, are a leading complication of childbirth. These conditions are defined as PMADs when presenting during pregnancy or within 1 year postpartum.

Up to 13% of women with normal pregnancies and 26% with adverse perinatal outcomes experience PMADs. Depression and anxiety often co-occur in pregnancy, and almost 50% of PMAD cases are never identified, increasing morbidity.

An early PMAD diagnosis allows optimization of maternal and fetal outcomes, but structured diagnostic interviews require a trained clinical diagnostician for accuracy, indicating a need for a new paradigm. Gamma aminobutyric acid–related neurotransmitter functioning has been considered for determining PMADs.

To evaluate the association between PMADs and maternal plasma protein signatures, investigators conducted a prospective cohort study. Participants aged over 18 years were enrolled between January 2017 and June 2020 at an academic medical center.

Patients in the investigation grouphad an available third-trimester plasma sample and PMAD symptom screening during the third trimester and at 3 months postdelivery. Those in the control group had a third-trimester plasma sample but did not have PMAD symptoms at screening. Structured diagnosis interviews were not used to confirm PMAD diagnoses.

Exclusion criteria included being a current smoker, HIV positive, engaging in substance abuse, having multiple gestations, or taking medications which affect the inflammatory response. The Research Electronic Data Capture tool was used to collect and manage study data.

Depression symptoms were assessed using the 10-item Edinburgh Postnatal Depression Scale, with higher scores indicating worsened symptoms. Scores ranged from 0 to 30, and scores of 12 or higher determined clinically elevated symptoms.

Anxiety symptoms were assessed using the 5-item Overall Anxiety Severity and Impairment Scale. Scores ranged from 0 to 20, and scores of 7 or higher determined clinically elevated symptoms. 

Distress, including traumatic birth, was measured using the 15-item Impact of Event Scale. Scores ranged from 0 to 75, and scores of 26 or higher indicated clinically elevated symptoms.

Plasma samples of 50 μL were assessed using the SOMAscan Assay 1.3k. Plasma sample tests included 5 pooled human plasma control cases and 1 no protein buffer control. Principal component analysis (PCA) with the XLSTAT software (Addinsoft, Long Island City, NY) was used to perform sample clustering.

Sociodemographic characteristics did not differ between patients at risk of PMADs and those not at risk except for parity, with 86.7% of women at risk and 44.4% of controls being multiparous. Depression, anxiety, and posttraumatic stress symptoms were significantly more common in women at risk of PMADs.

Significant differences in expression levels of plasma for PMAD patients compared to controls were found for 53 of 1305 proteins, with 9 being higher and 44 being lower. When evaluating the top 20 proteins with PCA, investigators found there were 2 dimensions where most of the PMAD group separated from the controls.

Of the variance, 34.72% was attributed to the first principal component, while 12.88% was attributed to the second principal component. Investigators found that differential protein expression could be categorized based on their roles in physiological functions.

These results indicated variance in plasma protein signatures based on PMAD risk status. Investigators recommended further studies to evaluate if these molecules can be used alongside traditional risk factors to determine PMAD risk.


Accortt E, Mirocha J, Zhang D, Kilpatrick SJ, Libermann T, Karumanchi SA. Perinatal mood and anxiety disorders: biomarker discovery using plasma proteomics. American Journal of Obstetrics & Gynecology. 2023;229(2):66.E1-66.E16. doi:10.1016/j.ajog.2023.01.012

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