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Approved Research

Characterizing the genetic and biological heterogeneity of Alzheimer's disease risk

Principal Investigator: Dr Jeremy Elman
Approved Research ID: 63648
Approval date: January 12th 2021

Lay summary

Alzheimer's disease (AD) is often thought of as a single disease with a standard set of features. However, research suggests there is much variability across people. For example, prior studies find individuals can have different types of cognitive impairment ("cognitive subtypes"). People can also show different patterns of tissue loss or pathology across the brain ("biological subtypes"). Interestingly, the different patterns of brain changes are associated with different cognitive impairments. This suggests that even "typical" AD may represent multiple disease subtypes. It is unclear whether these subtypes have different causes that require different treatments. Examining genetic risk can help us answer this question, yet hundreds or thousands of genes may be involved in a disease like AD. One approach is to sum all of these effects into a single value for each person, known as a polygenic risk score (PRS). However, this only considers risk along a single continuum: high versus low. Two individuals might have the same risk score, but very different patterns of which genes are contributing to this risk. These differences may cause different forms of the disease. This project will seek to identify genetic subtypes of AD by creating multiple PRSs for each person that summarize risk in sets of genes with related effects, often referred to as biological pathways.

This project will address two key questions: 1) Does the genetic risk for AD exist along multiple dimensions, not just high versus low; and 2) how does variability in the genetic risk for AD relate to the differences in the disease we see at the level of brain and cognition? The specific aims are to: 1) determine whether there are subtypes of AD genetic risk using PRSs specific to biological pathways; 2) test whether different patterns of brain tissue loss and pathology are associated with different forms of AD genetic risk; and 3) examine whether differences in cognitive impairment are associated with different forms of AD genetic risk. The project will use UK Biobank data to identify genetic and biological subtypes of AD that will be used to test for relationships in independent. The project duration will be ongoing, with an initial period of 36 months. Understanding the genes and biological pathways that may cause different types of AD will improve efforts to determine which types of treatment are likely to be most effective for each AD subtype.