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A comprehensive platform for analyzing longitudinal multi-omics data

ABSTRACT: A comprehensive platform for analyzing longitudinal multi-omics data

PROVIDER: PRJNA789262 | ENA |

REPOSITORIES: ENA

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A comprehensive platform for analyzing longitudinal multi-omics data

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Longitudinal multi-omics reveals subset-specific mechanisms underlying irritable bowel syndrome

Project description:The gut microbiome has been implicated in multiple human chronic gastrointestinal (GI) disorders. Determining its mechanistic role in disease pathogenesis has been difficult due to the apparent disconnect between animal and human studies and a lack of an integrated multi-omics view in the context of disease-specific physiological changes. We integrated longitudinal multi-omics data from the gut microbiome, metabolome, host epigenome and transcriptome in the context of irritable bowel syndrome (IBS) host physiology. We identified IBS subtype-specific and symptom-related variation in microbial composition and function. A subset of identified changes in microbial metabolites correspond to host physiological mechanisms that are relevant to IBS. By integrating multiple data layers, we identified purine metabolism as a novel host-microbial metabolic pathway in IBS with translational potential. Our study highlights the importance of longitudinal sampling and integrating complementary multi-omics data to identify functional mechanisms that can serve as therapeutic targets in a comprehensive treatment strategy for chronic GI diseases.

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Personal Omics Profiling Reveals Dynamic Molecular Phenotypes and Actionable Medical Risks

Project description:We have determined the whole genome sequence of an individual at high accuracy and performed an integrated analysis of omics profiles over a 1.5 year period that included healthy and two virally infected states. Omics profiling of transcriptomes, proteomes, cytokines, metabolomes and autoantibodyomes from blood components have revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways that occurred during healthy and disease states. Many changes were associated with allele- and edit-specific expression at the RNA and protein levels, which may contribute to personalized responses. Importantly, genomic information was also used to predict medical risks, including Type II Diabetes (T2D), whose onset was observed during the course of our study using standard clinical tests and molecular profiles, and whose disease progression was monitored and subsequently partially managed. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states. Examination of blood component in 20 different time points over 1.5 years which includes 2 disease state and 18 healty state Related exome studies at: SRX083314 SRX083313 SRX083312 SRX083311

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