Indices of Microbial Diversity Relating To Health

Abstract

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.

1 . A method comprising:
 a) predicting a state of a health condition in a subject by:
 i) providing a microbiome sample (e.g., a gut, vaginal canal, endometrial cavity, saliva, cell bound or cell containing or other biological fluid derived microbiome sample from a subject; 
 ii) determining, from the sample, a quantitative measure of microbes in one or a plurality of selected microbial genera; and 
 iii) applying a model to the quantitative measure to predict a state of the health condition; and 
   b) recommending or administering to the subject an intervention selected from a food, a supplement, a probiotic, a lifestyle change or pharmaceutical in an amount or degree sufficient to alter or maintain the state of the health condition.   
     
     
         2 . The method of  claim 1 , wherein the state of the health condition is given as a score, and altering the state of the health conditions comprises altering the score. 
     
     
         3 . The method of  claim 1 , further comprising monitoring the state of the health condition in the subject over a period of time by repeating operations (i), (ii) and (ii) one or a plurality of times. 
     
     
         4 . The method of  claim 1 , wherein the health condition is overweight Body Mass Index with Type II diabetes, and the selected microbial genus is taxonomic grouping “929”. 
     
     
         5 . The method of  claim 4 , wherein the quantitative measure is a relative amount of microbes belonging to taxonomic grouping “929” to total microbes. 
     
     
         6 . The method of  claim 5 , wherein the model predicts that overweight Body Mass Index with Type II diabetes is present when the relative amount is above a threshold percent. 
     
     
         7 . The method of  claim 1 , wherein the health condition is normal BMI with ulcerative colitis, and the selected microbial genus is taxonomic grouping “327”. 
     
     
         8 . The method of  claim 7 , wherein the quantitative measure is a relative amount of microbes belonging to taxonomic grouping “327” to total microbes. 
     
     
         9 . The method of  claim 8 , wherein the model predicts that normal BMI with ulcerative colitis is present when the relative amount is above a threshold percent. 
     
     
         10 . The method of  claim 1 , wherein the health condition is overweight Body Mass Index with Type II diabetes, and the selected microbial genus is taxonomic grouping “878”. 
     
     
         11 . The method of  claim 10 , wherein the quantitative measure is a relative amount of microbes belonging to taxonomic grouping “878” to total microbes. 
     
     
         12 . The method of  claim 1 , further comprising altering the intervention over the period of time to maintain the state of the health condition or alter the state of the health condition to a desired state. 
     
     
         13 . A method comprising:
 a) accessing by computer, a dataset comprising, for each of a plurality of subjects, (1) a medically verified state of one or a plurality of health conditions, and (2) quantitative measures of amounts of microbes belonging to one or a plurality of selected microbial genera in a microbiome of the subject; and   b) performing statistical analysis on the dataset to develop a model that predicts the state of the health condition in a subject based on the quantitative measures.   
     
     
         13 - 66 . (canceled) 
     
     
         67 . A system comprising:
 (a) a computer comprising:
 (i) a processor; 
 (ii) a memory, coupled to the processor, the memory including a quantitative measure of microbes in one or a plurality of selected microbial genera, and a model that, when executed, uses the quantitative measure or measures to predict a state of a health condition for the subject; and 
 (iii) computer executable instructions for implementing the classification rule on the data. 
   
     
     
         68 - 73 . (canceled)