Cardiometabolic Health Across the Female Life Course: Integrating Longitudinal Real-World Data and Multimodal Cohort Research for Precision Prevention

Cardiometabolic diseases, including cardiovascular disease, type 2 diabetes, obesity and hypertension, represent a major public health challenge. Their development is influenced by complex interactions between genetics, biological, hormonal, metabolic, environmental and lifestyle factors throughout the life course.

We propose to leverage Clalit Healthcare extensive longitudinal electronic health records and real-world clinical database to investigate cardiometabolic trajectories across women's life stages, with a particular emphasis on midlife and the menopausal transition.

The project will combine two complementary research approaches:

1. Large-scale longitudinal real-world data research

Using Clalit's extensive longitudinal clinical database, the project will:

• Characterize cardiometabolic trajectories across women's life course.

• Identify early clinical, demographic and longitudinal predictors of cardiovascular and metabolic diseases.

• Examine the contribution of traditional and emerging risk factors to cardiometabolic disease development, including genetic predisposition.

• Apply advanced statistical modelling, machine learning and AI to identify distinct cardiometabolic phenotypes, predict future disease risk and uncover potentially modifiable risk factors.

2. Development of a prospective longitudinal multimodal cohort of midlife women

Design and establish a prospective longitudinal cohort of midlife women, focusing on the menopausal transition and its implications for cardiometabolic health.

The cohort will provide an opportunity to investigate the interplay between genetics, hormonal changes, metabolic adaptation, lifestyle and cardiovascular risk during midlife, and to identify early biomarkers and trajectories associated with adverse long-term health outcomes.

Our ambition is to establish a multidisciplinary European collaboration that combines large-scale real-world evidence with deep longitudinal phenotyping to advance understanding of cardiometabolic health during women's midlife and translate this knowledge into more effective, personalized and equitable prevention strategies.