Multiple lines of evidence suggest microbial infections are risk factors for Alzheimer?s disease (AD). Amyloid-? (A?) peptides possess antimicrobial activity and may protect against human herpes viruses (HHV). Viral DNA is also detectable in A? plaques, and HHV DNA detected in next generation sequencing (NGS) experiments is associated with AD risk. Although neuroinflammation is the mechanism assumed to drive this association, several questions remain. Foremost, it is unclear whether infections precede AD or are the result of an aging immune system or AD pathology itself. The specific aspects of AD pathology that are affected by infections are also unknown, as is the role of the host genome in mediating risk. The objective of this project is to answer these questions by leveraging large AD cohorts with NGS data derived from blood and brain samples to detect the presence of microbial DNA. Microbial DNA can be detected and quantified in human NGS experiments by aligning reads that do not map to the human genome to microbial reference genomes, and depending on the species identified, may be evidence of either an active or latent infection. Any microbe for which a reference genome is available can be detected. The cohorts include the Alzheimer?s Disease Sequencing Project (ADSP), the Alzheimer?s Disease Neuroimaging Initiative (ADNI), the Framingham Heart Study (FHS), Accelerating Medicines Partnership-Alzheimer's Disease (AMP-AD), and Gwangju Alzheimer's & Related Dementias project (GARD). The long-term goal of this project is to provide evidence that interventions targeting microbial infections could prevent AD or slow its progression. Our central hypothesis is that infections increase AD risk and cause observable changes to specific facets of AD pathology. We also hypothesize that variants in the human genome mediate these processes. We will test these hypotheses through the following specific aims. In Aim1, we will develop a pipeline to accurately quantify and match DNA fragments generated by next generation sequencing to microbial DNA sequences, including inserted viral DNA. In Aim2, we will leverage longitudinally followed cohorts with multi-omics data to establish a temporal relationship between infection and AD, and test for associations between microbial DNA and AD-related traits, including biomarkers, structural brain changes measured by magnetic resonance imaging, neuropathological traits, disease progression, brain cell type sub-fractions, and cognitive function. In Aim3, we explore the role of the host genome in mediating microbe induced AD pathology, including testing for associations between SNPs and microbes, and for interactions between known AD risk variants/HLA serotypes and microbial DNA to predict AD. This project is significant because it could provide evidence that preventing or treating infections could treat or prevent AD. The project is innovative because it will be the first to leverage very large AD NGS cohorts, in many of which the tissue used for DNA sequencing was collected prior to AD diagnosis, and use case-only analysis to link microbial DNA to specific aspects of AD pathology.