Rethinking Neurodegeneration Through the Lens of Endocrine Transition
Neurodegenerative diseases, including Parkinson’s and Alzheimer’s disease, exhibit striking sex differences in prevalence, risk, and progression. Yet the endocrine transitions that may shape this vulnerability remain largely under-modeled in experimental systems. In this talk, I will present a framework positioning menopause as a neuroendocrine transition state that remodels circuit stability, inflammatory tone, and brain-body communication. Using a mechanistic model of accelerated ovarian failure, we investigate how dynamic hormonal fluctuations alter neuronal vulnerability and neuroimmune dynamics. I will present unpublished findings from our laboratory suggesting that endocrine instability – rather than chronological aging alone – acts as a systems-level modifier of disease trajectory. By integrating circuit neuroscience, gene therapy, and sex-informed modeling, this work advances a biologically grounded framework for studying and targeting neurodegenerative vulnerability.
Bio: Roberta Marongiu is an assistant professor of genetics and neuroscience at Weill Cornell Medicine. Her research focuses on how biological sex and menopause shape brain vulnerability in aging and neurodegenerative disease.
Marongiu earned her Ph.D. in medical genetics and neuroscience at Sapienza University of Rome, training with Enza Maria Valente during the discovery of the Parkinson’s disease-associated gene PINK1, contributing to the establishment of mitochondrial dysfunction as a central mechanism in Parkinson’s pathogenesis. She completed her postdoctoral training at Weill Cornell Medicine with Michael Kaplitt, where she developed AAV-based gene therapy strategies targeting Parkinson’s motor and non-motor symptoms.
Her laboratory now integrates AAV-mediated gene therapy, circuit-level neuroscience, and innovative models of menopause to investigate how endocrine transitions remodel dopaminergic, hippocampal, and gut-brain circuits in Parkinson’s and Alzheimer’s disease. Bridging mechanistic experimentation with computational approaches, her group leverages large-scale electronic health records, patient-derived datasets, and machine learning frameworks to model disease trajectories, define sex-specific risk architecture, and identify therapeutic targets and drug repurposing opportunities. Her work is supported by the NIH and major foundations, and she serves in international leadership and editorial roles, and patient’s organizations advancing sex-informed precision medicine in neurodegeneration.