Aging is a major risk factor for cognitive decline and increases the vulnerability of the brain to neurodegenerative diseases, such as Alzheimer’s disease (AD) which, in turn, dramatically accelerates cognitive deterioration and increases the risk for dementia. The biological pathways linking aging and AD are still poorly understood, partly due to the multitude of alterations induced by both processes. Identifying biological processes operating at the intersection of aging and AD that convey downstream effects on cognitive decline could enhance our understanding of the aging brain. Furthermore, these processes could provide efficient drug targets since their modulation would simultaneously affect two major determinants of dementia. To identify these processes, ADPriOMICs will combine extensive genome-wide genotype and gene expression data, sequencing information, proteomics, and deep phenotyping in longitudinal cognitive data using an unbiased approach. By combining frequentist and Bayesian statistics, and multiple layers of internal replication, we will select those genes/proteins most strongly and consistently linked with AD and aging (implicating shared pathways of action, with possibly maximum therapeutic potential), or with AD alone, or with Age alone (implicating distinct pathways, which still might yield novel and druggable targets). Based on prior, hypothesis-driven research, we expect that we will find enrichment for inflammation-related pathways, including microglia activation, in genes/proteins which are affected by both aging and AD pathology. ADPriOMICs has gathered a team of leading experts in the field of neuroinflammation, epidemiology, genetics, neuropsychology, and clinical research. ADPriOMICS has access to state-of-the-art methodology and know-how on inflammation. We will disentangle CSF proteomics (oLINK Explore panel) related to AD, aging, and cognitive decline using the information from 997 memory clinic patients with longitudinal data (Work Package [WP] 1). This information will flow into WP2 which will leverage large-scale GWAS on AD, cell-type specific gene expression data, and protein network analysis to identify drug targets and predictive markers. Next, WP3 will further validate drug target candidates based on whole exome sequencing (WES) which allows for assessing the effect of life-long alterations in protein function. Here, we will use data from a total of 49,517 participants and leverage an extreme phenotype design consisting of individuals with early onset AD (90 years which help to disentangle the influence of aging and AD (sample size extreme phenotypes: N=14,819, including new WES data on 3,000 individuals generated by ADPriOMICs). WP4 will combine information from WPs 1-3 to decipher the biological pathways in the intersection of aging and AD, thus also testing the inflammation hypothesis. Furthermore, potential drug targets supported by multiple layers of evidence will be tested using pharmacoepidemiological data. WP5 will use stem-cell-based AD cell models and CRISPR/Cas9 engineering to examine the most promising “shared pathway” genes. Finally, based on information from proteomics and genetics, WP6 will derive novel proteomic biomarker signatures of AD and aging which improve dementia prediction beyond established markers. In sum, ADPriOMICs will provide new perspectives on the biology of aging and dementia and has great potential to provide biologically prioritized, druggable entry points to address the dementia burden in aging populations.

Arithmetic groups, and more generally groups of matrices with integral entries are an object of interest in geometric group theory, number theory and differential geometry and manifold topology. Our project integrates all these aspects. A central theme is the relation of the geometric structures associated to these groups via locally symmetric spaces, to their topology.