Genetic dissection of the 17q21.31 MAPT locus in neurodegenerative disease

About This Grant

PROJECT SUMMARY / ABSTRACT Alzheimer’s disease and related dementias manifest with age-related progressive cognitive decline. Beyond sharing various aspects of their clinical and neuropathological presentation, these diseases are thought to also share genetic drivers, but those remain poorly characterized. One region on the long arm of chromosome 17 has been associated with risk for Alzheimer’s disease and more than 6 other neurodegenerative diseases, as well as multiple neurodevelopmental and non-brain diseases. This locus has been nicknamed the “MAPT locus” due to the presence of the microtubule-associated protein tau (MAPT) gene within this region. Abnormal deposits of the tau protein are linked to many neurodegenerative diseases. However, evidence suggests that MAPT is not the only gene that mediates disease risk in this large and gene-rich locus. Here we propose to leverage the genetic variation at the MAPT locus to pinpoint potential drivers of the diverse set of neuro- pathologies associated with this locus. The reason that these disease drivers remain unknown is that the MAPT locus is one of the most genetically complex loci in the human genome. During evolution, the locus underwent an inversion that flipped the orientation of approximately 14 genes. This inversion prevents recombination, creating two distinct alleles or “haplotypes”, named H1 and H2, within the human population. These haplotypes have diverged over time and now are distinguished by 2351 genetic variants in addition to the inversion itself. Which of these genetic variations drive disease risk and how? Why are some neurodegenerative diseases associated with the H1 haplotype while others are associated with the H2 haplotype? And to what extent does the inversion itself influence gene expression and disease susceptibility? To answer these questions, we will deploy our expertise in statistical genetics, machine learning, and functional genomics and dissect the molecular differences between the H1 and H2 haplotypes. First, we will analyze hundreds of publicly available single-nucleus multi-omic datasets to nominate genetic variants likely to impact gene expression and the brain cells in which they exert their effects (Aim 1). We will then pinpoint which of these prioritized variants are functional by engineering them into induced pluripotent stem cells and determining whether they impact gene expression once the cells are differentiated into brain cells (Aim 2). Finally, we will dissect the contribution of the inversion itself, providing, for the first time, an understanding of how the inversion has re-wired gene expression and cellular phenotypes (Aim 3). In all, our work will uncover how this enigmatic genetic locus impacts the cell types of the brain. This will provide key insights into how it is associated with such a diversity of diseases and nominate putative driver genes whose effects could be counteracted in the future with novel therapeutic interventions.