Understanding, predicting, and treating depression in pregnancy to improve mothers' and offspring's mental health outcomes: The HappyMums study

Abstract

Background: Perinatal depression is common: on average, more than 13% of women suffer from physician-diagnosed disorder and 20% report symptoms bearing clinical relevance. Maternal depression not only significantly impacts women's quality of life but also increases the offspring's risk of negative developmental outcomes, including mental disorders, through a combination of maternal alterations in in-utero biology and postnatal rearing factors during the early period of life. The HappyMums project aims to improve our understanding of perinatal depression by identifying the factors that robustly predict risk and resilience in mothers and their offspring, determining underlying neurobiological mechanisms, and, finally, testing the efficacy of potential interventions.

Methods: HappyMums will use data from a large collection of cohorts and registries containing biological, clinical, socio-demographic, environmental, and lifestyle data. It will pool unique human samples of maternal blood, placenta, chorionic villi and amniotic fluid, analyzing these data alongside pre-clinical samples of brain, blood and placental tissue from models of prenatal stress in mice and livebearing fish for correlative analyses. HappyMums will develop a mobile application (App) to collect multiple data types from women for early screening and monitoring of depressive symptoms.

Conclusion: The findings generated by HappyMums will be clinically relevant as they will increase the knowledge on perinatal depression, with unprecedented benefits for the offspring and the society as a whole.

Keywords: Biological mechanisms; Intergenerational transmission; Offspring; Perinatal depression; Pregnancy; Risk factors.

Fig. 1

The different Concepts within the HappyMums Study The HappyMums project will develop five different concepts. Concept 1 will aim to identify multimodal predictors for depressive symptoms, their progression, and response to interventions. Concept 2 will aim to identify the biological signatures and markers linking maternal depressive symptoms to offspring outcomes together with the assessment of the role of postnatal factors as moderators. Concept 3 will take advantage of preclinical mouse and fish models to investigate the neurobiological mechanisms and peripheral biomarkers. Concept 4 will focus on personalized strategies to improve mental health in pregnant women using machine learning approaches and digital tools. Lastly, Concept 5 will investigate the effects of pharmacological and non-pharmacological interventions in pregnancy and the underlying biological mechanisms.

Fig. 2

The biology of perinatal depression and the consequences on the exposed offspring The project aims to investigate how perinatal depression affects not only the mental health of the mothers but also the intrauterine environment and biology, negatively impacting the developing foetus and shaping the offspring's risk for the development of psychopathology later in life.

Fig. 3

Graphical representation of the Concept 3 experimental paradigm of the three rodent models In the HappyMums project, three complementary rodent models will be included that incorporate distinct aetiological risk factors of maternal depression. These three models will allow a longitudinal postnatal assessment of behavioural functions in offspring as well as molecular signature in blood and brain in relation to the behavioural outcome.

Fig. 4

Graphical representation of the Concept 3 experimental paradigm of the novel live-bearing fish models In the HappyMums project, four closely related live-bearing fish species from the family Poeciliidae will be included, of which two have a placenta and two lack a placenta. These fish models will allow comparisons between closely related livebearing species with and without placentas to elucidate specifically the role and mechanisms of the placenta in transferring the adverse effects of maternal depression during pregnancy to the developing offspring in utero.

Fig. 5

HappyMums platform components and interactions The HappyMums digital platform is composed of: A) an App for pregnant women meant for screening risk detection and symptoms monitoring; B) a clinical dashboard for clinical data collection and patient monitoring; this platform backend will run on a cloud-based infrastructure that will manage data storage, data processing and data exchange between components.

Fig. 6

Representation of HappyMums App The HappyMums App for women will allow data collection, and specifically data will be generated by three different means: A) Manual data entry (completing questionnaires and periodically reporting medical and biological data); B) Active interaction with the system (voice analysis and facial expression modules and execution of game-like exercises); C) Passive monitoring (background collection of data coming from smartphone embedded sensors, such as physical and social activity).