Making a difference - polygenic risk score for Alzheimer's disease

 

UCLH BRC-supported research into the genetic variations responsible for harmful protein build-up in the brain has led to tests that can predict the inherited risk of developing Alzheimer’s disease. In collaboration with a biotech company the tests have been developed into a diagnostic product, genoSCORE, to help identify sufferers and aid drug discovery, now available to the pharmaceutical industry in the EU and UK.

Alzheimer’s disease (AD) is the leading cause of dementia in older people, affecting one in 14 people over 65 in the UK, due to a decade-long build-up of the protein amyloid in the brain. Removing amyloid or preventing its accumulation is a priority for Alzheimer’s treatment. However, anti-amyloid therapy is most effective early in the disease process. Simple and effective tests to identify who is most likely to develop amyloid build-up are urgently needed to ensure patients receive the most appropriate treatment and also to support clinical trial recruitment.

John Hardy and his postdoc Maryam Shoai have improved the diagnostic accuracy of genetic analysis in very early detection of amyloid deposition. Their research highlighted that genetic analysis in clinical diagnosis was only about 75% accurate and even less so in very early stages of the disease. 1

Using a database of genomes from over 17,000 individuals they identified more than 40 areas of the human genome linked to increased risk of AD (risk loci). They used this information to develop a ‘polygenic risk score’ (PRS) for AD.

To convert the PRS analysis into an efficient diagnostic tool, the UCLH BRC team worked with genetics start-up company Cytox to develop a streamlined test genomes associated with AD risk and an analysis pipeline that now provides accurate, high-volume diagnosis of disease. genoSCORE is now approved and marketed to pharmaceutical companies to aid early diagnosis and patient. It is now also being adapted for clinical diagnostic use. 2

Using the UCL-hosted 1946 British birth cohort biobank that contains longitudinal genomic and clinical data from 5,362 individuals, the team is now exploring how genetic determinants influence the way AD progresses. They plan to develop a polygenic risk score that can be linked to the rate of patient decline and disease progression, which will support better clinical trial design and effective patient management.

1. Escott-Price, V. et al., Neurobiol. Aging, 2019; 2. Daunt, P. et al., J. Prev. Alzheimer’s Dis, 2021