Research News

DEMON Webinar Recording: Precision Molecular Epidemiology

Precision Molecular Epidemiology: Linking risk factors to statistical prediction, prevention, and clinical translation.

This talk by Dr Natàlia Vilor-Tejedor was recorded ion 11th February 2026 by the DEMON Network Biomarkers Working Group.

Dr Natàlia Vilor-Tejedor holds a doctorate in Biomedicine from Pompeu Fabra University, and specializes in biostatistics and neurogenetics. She works as a researcher at the BarcelonaBeta Brain Research Centre & Institute of Risk Assessment and Science, Utrecht University. She is responsible for the Genetic Neuroepidemiology and Biostatistics team, dedicated to researching the biological mechanisms and genetic profiles of preclinical Alzheimer’s.

In this conversation, Natalia discusses her research in precision molecular epidemiology, focusing on the connections between risk factors, genetics, and environmental influences on brain health, particularly in relation to Alzheimer’s disease. She emphasises the importance of understanding both genetic and environmental factors, the role of neuroinflammation, and the need for diverse representation in research. Natalia also highlights innovative methodologies in data analysis and the significance of translating research findings into public health policies.

Find out more about Natalie and her work:
https://www.adamslab.nl/team/natalia-vilor-tejedor/

Find out more about the DEMON Network and how you can get involved in their work:
https://demondementia.com/

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DEMON Network

DEMON is an international network for the application of data science and AI to dementia research. The Deep Dementia Phenotyping (DEMON) Network brings together academics, clinicians and other partners from across the world. By connecting these people, we can identify innovative approaches to interdisciplinary collaborative dementia research across multiple institutions.

Our vision is to revolutionise dementia research and healthcare by bringing innovators together and harnessing the power of data science and AI.

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