The BEACON Consortium
Dementia frontiers fund
Biomarker Estimation of Absolute Cognitive impairment risk in Older adults transNationally
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Led by
Professor Clifford Jack Jr. and Professor Ronald Petersen (Mayo Clinic)
Locations
USA, Spain and Australia
Research question
Can we better predict and stage disease progression in dementia?
Research institutions
4
Together with
Professor Beverly Gwen Windham (University of Mississippi), Professor Christopher Rowe (University of Melbourne), Professor Arcadi Navarro (Barcelonaβeta Brain Research Center), Dr Alicia Algeciras Schimnich (Mayo Clinic), Dr Maria Vassilaki (Mayo Clinic), Dr Prashanthi Vemuri (Mayo Clinic), Dr Jonathan Graff-Radford (Mayo Clinic), Dr Mingzhao Hu (Mayo Clinic), Professor Michael E. Griswold (University of Mississippi), Dr Hunter Sylvester (University of Mississippi) and Assistant Professor Srishti Shrestha (University of Mississippi)
Project summary
This project will develop and validate a multinational risk prediction framework to estimate an individual’s absolute risk of progressing to mild cognitive impairment (MCI) or dementia over defined time horizons and across the remaining lifespan.
As blood-based biomarkers and disease-modifying therapies become increasingly available, there is a growing need for clinically useful tools that can support personalised treatment and prevention decisions.
Existing approaches often estimate relative risk and frequently fail to account for important factors such as competing mortality risk and bias introduced by participant dropout, limiting their clinical applicability.
The programme brings together four large longitudinal cohorts from the United States, Australia and Spain to create a harmonised dataset incorporating clinical, demographic, genetic and biomarker information.
A central innovation is the integration of plasma p-tau217, a scalable biomarker of Alzheimer’s disease pathology, with MRI measures of cerebrovascular disease, including infarcts, white matter hyperintensities and diffusion imaging markers.
The team will also establish new procedures to capture deaths and dementia diagnoses among participants who are no longer actively followed, improving the accuracy of lifetime risk estimates.
Using these harmonised data, the researchers will construct a Multi-State Hidden Markov Model capable of generating personalised predictions of future cognitive decline. The resulting platform will provide an accessible, evidence-based risk calculator designed to support clinical decision-making, participant stratification and future preventative intervention strategies.
Plain English summary
This project will develop a tool that estimates a person’s risk of developing memory and thinking problems over the coming years.
By combining information from blood tests, health records and other known risk factors, the tool aims to provide individuals, families and healthcare professionals with clearer and more personalised information to support decisions about prevention, monitoring and treatment.
Potential future impact
This research could lead to more accurate and accessible ways of estimating an individual's risk of developing dementia, helping to support earlier and more personalised decision-making.
By incorporating emerging blood-based biomarkers and a broader range of factors that contribute to cognitive decline, the tool could become increasingly relevant to routine healthcare.
Validation across diverse international populations may help ensure that risk predictions are reliable for different groups and healthcare settings.
In the longer term, the approach could support more targeted prevention strategies, identify individuals most likely to benefit from new treatments, and help clinicians and patients make more informed choices about future care and disease management.