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Precision environmental health monitoring by longitudinal exposome and multi-omics profiling
Author(s) -
Peng Gao,
Xiaotao Shen,
Xinyue Zhang,
Chao Jiang,
Sai Zhang,
Xin Zhou,
Sophia Miryam SchüsslerFiorenza Rose,
M Snyder
Publication year - 2022
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.276521.121
Subject(s) - exposome , biology , phenome , omics , environmental epidemiology , profiling (computer programming) , computational biology , data science , bioinformatics , computer science , genetics , gene , phenotype , operating system
Conventional environmental health studies have primarily focused on limited environmental stressors at the population level, which lacks the power to dissect the complexity and heterogeneity of individualized environmental exposures. Here, as a pilot case study, we integrated deep-profiled longitudinal personal exposome and internal multi-omics to systematically investigate how the exposome shapes a single individual's phenome. We annotated thousands of chemical and biological components in the personal exposome cloud and found they were significantly correlated with thousands of internal biomolecules, which was further cross-validated using corresponding clinical data. Our results showed that agrochemicals and fungi predominated in the highly diverse and dynamic personal exposome, and the biomolecules and pathways related to the individual's immune system, kidney, and liver were highly associated with the personal external exposome. Overall, this data-driven longitudinal monitoring study shows the potential dynamic interactions between the personal exposome and internal multi-omics, as well as the impact of the exposome on precision health by producing abundant testable hypotheses.

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