Research focus
Estrogenic neuroprotection in Alzheimer’s disease
Estrogen is neuroprotective and exerts its functions through estrogen receptors. Loss of estrogen at menopause has been proposed as a risk factor in Alzheimer’s disease (AD) and a contributing factor to the sex differences observed in this disease. We study neuroprotection mediated through a specific estrogen receptor, estrogen receptor beta (ERb), using selective and clinically relevant estrogen receptor ligands in combination with ERb knockout in models of AD. We also study the impact on systemic sex hormone depletion and menopausal hormonal therapy in modulating brain energy homeostasis, risk of AD later in life, and on hallmarks of AD pathology. For this we integrate experimental models (including brain organoid models) with human epidemiological data. In this way we hope to provide new understanding to why more women than men are diagnosed with AD.
Gender affirming hormone therapy and the aging brain
Early adult change in hormone balance can be a risk factor for several diseases. However, knowledge here is almost completely missing. We study if gender affirming hormone therapy can modulate the risk of AD. For this we use an integrative approach, combining experimental and unique human cohort data. Understanding if there are health risks with gender affirming hormone therapy and which possible early preventive measures can be implemented is key to the healthy aging of these individuals and can minimize stigmatization.
Interaction between endocrine and environmental stress on mental health
Mental health issues are a growing problem in society. To address this challenge, today’s symptom-based treatments must be complemented with individual- and gender-specific approaches based on biological criteria. We are part of the Re-MEND EU project in which we aim to identify risk and resilience factors to anxiety and depression across endocrine sensitive life stages; early development, puberty, pregnancy & postpartum, and transition into older age. The project combines genetic, epigenetic, transcriptomic, proteomic, metabolomic and lipidomic profiling, with information on environmental exposures and health outcomes, and uses artificial intelligence to mine the data for risk and resilience factors across the endocrine sensitive life stages.