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Precision processing
Credit: UK Biobank/Wellcome Images

These areas of Dementias Platform UK look at optimising the way in which dementia is assessed and researched, and sets protocols and guidelines for researchers to follow.

outcomes adjudication

Led by Cathie Sudlow, University of Edinburgh

This team is working with real world data, looking to determine how this can help to better understand neurodegenerative diseases such as dementia. The aim is to produce robust methods to identify cases of dementia or other neurodegenerative disease, such as Parkinson’s or MND, from data routinely gathered by cohort studies, GPs, hospitals and death records.

cognitive assessment 

Led by John Starr, University of Edinburgh

This team works with UK Biobank to improve the cognitive testing that it administers, and focuses on implementing this in the 100,000 participants who are currently undergoing brain scans. They have developed an enhanced battery of computer-administered cognitive tests, which was rolled out at the UK Biobank imaging assessment at the end of 2016 – data collection is ongoing. They will be validating the cognitive measures that UK Biobank uses.

ethical, legal and social issues

Led by Carol Brayne, University of Cambridge

As dementia research is evolving, and with so much of DPUK’s work being a first for the sector, this work looks at the ethical issues arising from the project. It informs the governance structures for dementia experimental medicine involving cohorts, and ensures participants’ views and motivations for participation are considered throughout.

brain donation

Led by Carol Brayne, University of Cambridge

This work package develops methods and processes for implementing a sustainable and scientifically informative brain and iPSC (stem cells) donation programme for use by DPUK. It will identify the most informative cohorts for which brain donation would be desirable, as well as drawing up protocols for best practice.

Biostatistics - Genetics 

Led by Julie Williams, Cardiff University

This team has developed, and continues to advance, state-of-the-art risk stratification methods for Alzheimer’s disease using polygenic risk scores and other analytical techniques. These risk stratification algorithms are available for application to DPUK cohorts. They are preparing exemplar analyses to test the utility of the data portal for cross-cohort analyses linking genetic, population and routinely-collected data.

biostatistics - methods

Led by Sylvia Richardson, University of Cambridge

This group is developing statistical methods that will allow us to use DPUK cohort data, for example genetics and basic demographics, to differentiate those people who are more likely to develop dementia or deteriorate faster than others.

They are testing whether this can be done with both single as well as repeated measurements. They are also developing methods to see if it is possible to increase the certainty of predictions of who is at risk of developing dementia by combining a number of complex measures, including brain imaging, urine and blood biomarkers.