Pilot validation of blood-based biomarkers during pregnancy and postpartum in women with prior or current depression

E E Redei,S L Wert,A Yang,K L Wisner,K B Zumpf,S Kim,J D Ciolino,C Clark

doi:10.1038/s41398-020-01188-4

Abstract

Major depressive disorder (MDD) is more common in women than in men, and evidence of gender-related subtypes of depression is emerging. Previously identified blood-based transcriptomic biomarkers distinguished male and female subjects with MDD from those without the disorder. In the present pilot study, we investigated the performance of these biomarkers in pregnant and postpartum women with prior major depressive episodes, some of whom had current symptomatology. The symptom scores of 13 pregnant and 15 postpartum women were identified by the Inventory of Depressive Symptoms (IDS-SR-30) at the time of blood sampling. Blood levels of the 20 transcriptomic biomarkers and that of estrogen receptor 2 (ESR2), membrane progesterone receptor alpha and beta (mPRα, mPRβ) were measured. In pregnant women, transcript levels of ADCY3, ASAH1, ATP11C, CDR2, ESR2, FAM46A, mPRβ, NAGA, RAPH1, TLR7, and ZNF291/SCAPER showed significant association with IDS-SR-30 scores, of which ADCY3, FAM46A, RAPH1, and TLR7 were identified in previous studies for their diagnostic potential for major depression. ASAH1 and ATP11C were previously also identified as potential markers of treatment efficacy. In postpartum women, transcript levels of CAT, CD59, and RAPH1 demonstrated a trend of association with IDS-SR-30 scores. Transcript levels of ADCY3, ATP11C, FAM46A, RAPH1, and ZNF291/SCAPER correlated with ESR2 and mPRβ expressions in pregnant women, whereas these associations only existed for mPRβ in postpartum women. These results suggest that a blood biomarker panel can identify depression symptomatology in pregnant women and that expression of these biomarker genes are affected by estrogen and/or progesterone binding differently during pregnancy and postpartum.

Highlights

Depression is the fourth leading contributor to the global burden of disease and the second leading cause of disability in persons 15–44 years of age[1,2,3]
We evaluated each gene (ADYC3, AMFR, ASAH1, ATP11C, CADM1, CAT, CD59, CDR2, CMAS, DGKA, FAM46A, KIAA1539/FAM214B, MAF, MARCKS, NAGA, PSME1, PTP4A3, RAPH1, TLR7, and ZNF291/ SCAPER) individually for potential associations with symptom measures via a series of individual linear mixed models (LMMs)for IDS-SR-30 with random participant effect and fixed ΔCT effects
IDS-SR-30 scores were significantly associated with transcript levels of ADCY3, ASAH1, ATP11C, CDR2, estrogen receptor 2 (ESR2)

Summary

Introduction

Depression is the fourth leading contributor to the global burden of disease and the second leading cause of disability in persons 15–44 years of age[1,2,3]. The most commonly used approaches for the diagnosis of MDD are clinician-rated scales and selfreport assessments. A diagnostic test would be welcoming in primary care settings, where the majority of patients with MDD are treated[8]. The sensitivity of diagnosis in this setting is 50%, which suggests a large number of missed cases[9]. These and other data suggest that aiding MDD diagnosis in the primary care setting has the potential to significantly and positively affect precision of diagnosis and speed of treatment. Specificity of diagnosis is as essential as its reliability; biological markers correctly identifying MDD patients would greatly contribute to improving both

Objectives

Methods

Results

Conclusion