Indices of Microbial Diversity Relating To Health

    公开(公告)号:US20210324473A1

    公开(公告)日:2021-10-21

    申请号:US17204898

    申请日:2021-03-17

    摘要: Provided herein are methods for altering a health state of a subject by administering a wellness intervention to subjects found to have quantitative measures of microbial genera in the subject's microbiome that are associated with undesirable health states. Undesirable health states can be inferred by executing models that predict health states based on the quantitative measures, such as relative amounts of selected microbial genera to all microbes. Models are created by statistical methods that analyze datasets that include, for each of a plurality of subjects, verified health states and quantitative measures of each of a plurality of microbes classified at designated taxonomic levels, e.g., genus level.

    Indices of Microbial Diversity Relating To Health

    公开(公告)号:US20200270699A1

    公开(公告)日:2020-08-27

    申请号:US16852534

    申请日:2020-04-19

    摘要: Provided herein are methods for altering a health state of a subject by administering a wellness intervention to subjects found to have quantitative measures of microbial genera in the subject's microbiome that are associated with undesirable health states. Undesirable health states can be inferred by executing models that predict health states based on the quantitative measures, such as relative amounts of selected microbial genera to all microbes. Models are created by statistical methods that analyze datasets that include, for each of a plurality of subjects, verified health states and quantitative measures of each of a plurality of microbes classified at designated taxonomic levels, e.g., genus level.

    Indices of microbial diversity relating to health

    公开(公告)号:US10982283B2

    公开(公告)日:2021-04-20

    申请号:US16852534

    申请日:2020-04-19

    摘要: Provided herein are methods for altering a health state of a subject by administering a wellness intervention to subjects found to have quantitative measures of microbial genera in the subject's microbiome that are associated with undesirable health states. Undesirable health states can be inferred by executing models that predict health states based on the quantitative measures, such as relative amounts of selected microbial genera to all microbes. Models are created by statistical methods that analyze datasets that include, for each of a plurality of subjects, verified health states and quantitative measures of each of a plurality of microbes classified at designated taxonomic levels, e.g., genus level.