From population-based study to functional biology: combinatorial effect APOE and low-risk genetic risk factors of Alzheimer's Disease in the microglia response to amyloid pathology.

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.

Keywords:ALZHEIMER'S DISEASE, GENETIC RISK FACTORS

Disciplines:Computational evolutionary biology, comparative genomics and population genomics, Bioinformatics and computational biology not elsewhere classified, Molecular and cell biology not elsewhere classified, Neurosciences not elsewhere classified, Clinical genetics and molecular diagnostics