A Multidisciplinary Biomarker Platform to Determine the Effect of Sex-Specific Hormonal and Epigenetic Factors on Cardiovascular Disease Risk

During periods of hormonal change (menopause, postpartum, post-preeclampsia), the female cardiovascular system exhibits distinct epigenetic reprogramming and activation of molecular stress pathways. These signatures can be used for early diagnosis and risk prediction.

This project will be structured into an integrated set of work packages designed to uncover sex and gende specific molecular, hormonal, epigenetic, and socio-behavioural determinants of cardiovascular diseases (CVDs), with an emphasis on female-specific risk factors. The overall workflow spans mechanistic discovery, biomarker identification, multi-omics integration, population-level analysis, and clinical translation. The first component focuses on elucidating the biological mechanisms underlying sex differences in CVD by combining endothelial cell models, hormonal perturbation systems, and epigenetic profiling. By analysing the effects of estrogen deprivation, menopausal hormone shifts, and pregnancy related complications such as preeclampsia, we will identify key molecular pathways including inflammatory signaling, oxidative stress responses, vascular barrier regulation, and epigenetic reprogramming that differ between men and women and contribute to differential disease susceptibility.

Parallel to mechanism discovery, the project will establish a biomarker development pipeline to identify sex specific epigenetic signatures and circulating protein markers indicative of early vascular dysfunction. Biomarkers will be validated using in vitro models such as 2D/3D endothelial cultures and patient-derived samples from existing European cohorts. These datasets will feed into a comprehensive risk assessment framework integrating molecular data with clinical parameters and sex/gender related factors, including reproductive history, menopausal status, lifestyle behaviours, psychosocial stress, socioeconomic variables, and cultural determinants. Social sciences and humanities (SSH) experts will ensure that gender norms, behavioural patterns, and health-care access disparities are appropriately analysed and incorporated into risk prediction models.

Using advanced bioinformatics, AI supported modelling, and epidemiological datasets, the consortium will develop a sex- and gender tailored cardiovascular risk model, enabling personalised prevention and stratification strategies. Finally, clinical partners will support the validation of biomarker panels and risk algorithms in real world settings, paving the way for translational exploitation through diagnostic development and improved prevention strategies for women and men.