Among the known blood molecules is a new class, the extracellular RNAs (exRNAs.) Some of these are excellent biomarker candidates, but there are also a significant number of exRNAs derived from the microbiome. Both endogenous and exogenous exRNAs carry much information and could be effectors of cellular function. The NIH Common Fund exRNA consortium is now researching and applying exRNA in humans to diagnostics and therapeutics. A foundation for this effort, reliable profiles of the exRNA spectrum in healthy individuals, is needed. We have assembled an experienced, interdisciplinary team to carefully characterize these reference RNA profiles, and to improve the methods for doing so. The PI will work closely with Co-PI's Debbie Nickerson (UW Genomics Center co-Director, Sequencing), and Kai Wang (Institute for Systems Biology, data analysis), Co-Investigator, Elaine Peskind, VA Center and UW, selecting and providing samples), and co-investigators to provide advice, consultation, and collaboration (Paul Wilmes, Univ. of Luxembourg; Aleks Milosavljevic, Baylor; and Muneesh Tewari, Univ. of Mich.) We propose the generation, analysis, and dissemination of exRNA profiles of plasma, serum, CSF and saliva from the same healthy subjects: roughly equal numbers of men and women in three age categories (31 to 101 years.) These matched samples of serum, plasma, saliva and CSF collected at the same time from the same subjects are a key asset of this proposal. A new dimension in exRNA research was revealed by our recent work. The presence of microbial RNA (bacterial and fungal) in blood plasma raises important questions concerning its origins and functions. We will use our computational pipeline, including tools from the DMRR (DIAC), to characterize both endogenous exRNAs (en-exRNA) and exogenous exRNA (ex-exRNA) in and outside of lipid vesicles (in human serum, plasma, saliva and CSF.) We will do four NextGen libraries per sample: in and out of vesicles, and short and long insert libraries. We propose to characterize a set of 180 subjects over five years, and analyze and deposit profile data and metadata in the exRNA Atlas created and maintained by the DMRR of the ECRP consortium. We will complete the development and testing of a novel approach to generate sequence-specific library bias correction factors. We will periodically re-characterize the ex-exRNA due to microbial sequence database updates. The data generated will enable us to examine the variance in individual exRNAs and clusters of exRNAs as a function of subject attributes (including age and gender.) The project will be carried out in two phases. In the first phase (years 1 and 2), methods will be tested during data acquisition and analysis, including the bias correction method. The second phase (years 3-5) will consist of data generation and analysis only. A major emphasis and strength of our proposal is the rigorously collected, matched samples of multiple body fluids on the same subjects, with emphasis on accurate acquisition and analysis of exRNA and our extensive experience in all aspects of the proposed work.