Omics and Technology Core

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ABSTRACT – Core 1: Omics and Technology Core The Omics and Technology Core will act as a portal that interconnects all parts of the project, and will provide them with high-quality genomics, metabolomics and imaging data, to be integrated with the clinical and phenotyping information. To ensure maximal scientific output from the study samples, analysis will be conducted by leaders in each field and centers of excellence. The core will work closely with NCRAD, that will implement standardized procedures for collection of samples across the Alzheimer Centers, will coordinate shipment to our technology hubs for sample analysis, and enable tracking of chain of custody. The core will also work closely with the bioinformatics core and the Duke team to ensure gold-standard data management and to enable comprehensive data mining for the whole scientific community. The first sub-core will conduct state of the art metagenomics analysis of collected fecal samples to profile the entire microbial community inhabiting the gut. Genomic microbial DNA will be extracted and purified from the specimens using a commercially-available DNA kit, previously validated by the Human Microbiome Project. The culture- independent molecular methods will consist of shotgun metagenomic sequencing that provides the most comprehensive microbiota profile (bacteria, viruses, archaea, fungi). Rigorous sequence data analysis will utilize a set of advanced computational algorithms, according to the taxon-based or function-based data matrices. The second sub-core will conduct metabolomics analysis of blood and feces, to profile the host and gut-microbiota metabolomes. Comprehensive metabolome coverage is best achieved via combination of complementary approaches, and here we will apply various advanced methods of untargeted and targeted metabolomics. Untargeted metabolomics will utilize very high-resolution mass spectrometry (MS) to detect many thousands of compound spectra per sample, and employ complex algorithms and extensive data mining for identity elucidation. Conversely, targeted metabolomics platforms will utilize more sensitive and quantitative MS/MS measurement of only hundreds of compounds chosen according to existing evidence, biological interest and specifically the gut microbiome activity. Global metabolomics will be a cross-over between the two approaches, producing a full-scan high-resolution MS measurement of a few thousands of compounds, some identifiable via authentic standards, while others continuously added to the dynamic learning database of detected compounds, for further investigation. The third sub-core will gather quantitative magnetic resonance imaging of the brain, which contributes an additional layer to the phenotyping of the study participants. Building from the success of the ADNI project, a T1-weighted volumetric imaging will be utilized, to allow harmonization across the multiple sites. The imaging sub-core will coordinate the collection and aggregation of three- dimensional T1 imaging, and utilize existing ADCS image informatics infrastructure for high-throughput data capture, upload, and review.