Abstract
In the recent meta-analysis of Alzheimer's disease (AD) genome-wide association studies by Sleegers Lab, 39 known and 44 novel variants were reported to have significant genome-wide signals. Pathway- and single cell enrichment analysis points to microglia as the major responsible for this genetic risk. However, none of these risk factors can explain alone the development of AD. I hypothesized that unknown combinations of these variants may have the potential to better stratify AD patients and controls. To test my hypothesis, I used multifactor dimensionality reduction and logistic regression over the AD-Belgian-Flemish Cohort to search for the putative combinations of 85 genetic risk factors. The preliminary analysis identified numerous high-risk statistically significant combinations, mainly composed by APOE ?4 and low-risk genetic factors. To validate my results, I am running the same pipeline in the largest European cohort of AD patients, the European AD Biobank consortium, where I will parallelly correlate several clinical parameters with the presence of the combos described. To functionally validate the in silico analysis, I will employ cutting-edge technology to A) recapitulate top 3 combos' effect in human microglia (MG) by multiplex gene editing and B) xenotransplant the edited MG into the brain of AD-like mice following the MIGRATE protocol recently published by the Mancuso Lab.
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