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Updated 20/01/2022

Tackling dementia with data-driven risk factor prediction

In LETHE a broad approach to prevention of Dementia is built at the intersection of clinical and technological disciplines. The project is developing a data-driven risk factor prediction model for older individuals at risk of cognitive decline, novel digital biomarkers and a digitally enabled intervention.

During 2021, the LETHE clinical partners (Finnish Institute for Health and Welfare, Karolinska Institutet, Medical University of Vienna, University of Perugia) have been working closely together to harmonize data from the Finnish randomized controlled dementia prevention trial FINGER and large observational study cohorts in Austria, Italy, and Sweden.

These cohorts cover the full spectrum from at-risk persons from the general population to memory clinic patients with subjective cognitive complaints, mild impairment, and dementia.
The aim of this data harmonization process is to provide a pooled dataset which allows data-driven identification of risk factors for cognitive decline. Altogether, the team has been able to create >100 new harmonized variables that are shared by two or more datasets and can thus be used for joint analyses. These variables are related to cognitive and functional performance, to clinical characteristics such as medication use, to biomarkers, to sociodemographic factors, and to lifestyle.

This work provides a solid basis for the initial LETHE prediction modelling which will be conducted as part of the ongoing project activities.


EGI Foundation is a partner in LETHE, a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 101017405. As project partner, EGI Foundation is leading to design LETHE system architecture and to build data collection and big data framework including set-up of the LETHE big data infrastructure, set-up the authentication scheme for the LETHE project and registration of the LETHE infrastructure and services in EOSC.