Summary: This brief proposal is for an administrative supplement to our existing grant on ?A Systems Approach to Targeting Innate Immunity in AD.? We seek support for the integrated analysis team from the Mayo Clinic and Institute for Systems Biology to contribute to the consortium-wide vision for the next phase of multi-omics analysis of AMP-AD data to deliver on the overall goals of translating therapies for Alzheimer?s Disease, a massive global need. We have a seven year history of working closely together in this field, and a deep familiarity and expertise with the datasets from AMP-AD and the pre-symptomatic data from the Arivale cohort we are using to study effects of AD-associated genetics throughout lifespan. We have two primary aims for our work, that each map into the larger aims from the whole consortium vision for the next phase of multi-omics analysis. In Aim 1, our goal is to identify subtypes of Alzheimer?s disease and related disorders (ADRD) utilizing AMP-AD transcriptome data. The central hypothesis of Aim 1 is that unique pathways and characterizations of high dimensional gene expression data can be leveraged to classify and otherwise quantify the AD burden according to its neuropathologic underpinnings. In this aim, we will apply three distinct approaches (ANOVA regression, random forest, and convolutional neural networks) to identify groups of genes the expression levels of which can discriminate not only AD from controls, but subtypes of AD from one another and AD from other neurodegenerative conditions. These genes will then become candidate molecules that may be drivers of subtypes of ADRD and/or can also serve as panels of biomarkers that may distinguish these subtypes. These molecules will be validated using human and model system data from within and outside of AMP-AD. We will also evaluate the transcriptional regulatory networks and key regulators of the genes that differentiate the subtypes we will have identified. In Aim 2, we plan to work with the consortium to harmonize the CNS model of disease progression and peripheral measures of disease state. In particular, we will focus on integrating findings from peripheral tissues (such as protein and metabolite levels in blood and CSF) that begin with the evaluation of effects in peripheral tissues (mostly blood) of genetic risk factors for Alzheimer?s Disease (pre-symptomatic or asymptomatic effects) and then trace signals that map onto increasingly severe AD progression. Identifying individuals in preclinical AD, long before clinical symptomology and diagnosis, and then understanding the early stages of AD and how it progresses to its end stages is crucial for developing effective therapies and disease-delaying interventions. Peripheral tissues give us our best opportunity for monitoring these processes.