Method and system for microbiome-derived diagnostics and therapeutics for neurological health issues

Abstract

A method for at least one of characterizing, diagnosing and treating a neurological health issue in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the neurological health issue based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the neurological health issue; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

We claim: 
     
         1 . A method for characterizing chronic fatigue syndrome, the method comprising:
 at a sample handling network, receiving an aggregate set of samples from a population of subjects;   at a computing system in communication with the sample handling network, generating a microbiome composition dataset and a microbiome functional feature dataset for the population of subjects upon processing content of each of the aggregate set of samples, wherein processing content of each of the aggregate set of samples comprises processing nucleic content with a fragmentation operation, a multiplexed amplification operation using a set of primers, and a sequencing analysis operation;   at the computing system, receiving a supplementary dataset that is informative of chronic fatigue syndrome presence within the population of subjects;   at the computing system, transforming the supplementary dataset and features extracted from at least one of the microbiome composition and the microbiome functional feature datasets into a characterization model of chronic fatigue syndrome; and   based upon the characterization model, generating a therapy model configured to improve a health state of an individual diagnosed with chronic fatigue syndrome by the characterization model.   
     
     
         2 . The method of  claim 1 , wherein generating the characterization model comprises analyzing a set of features from the microbiome composition dataset with a statistical analysis, wherein the set of features includes features associated with at least one of: relative abundance of different taxonomic groups represented in the microbiome composition dataset, interactions between different taxonomic groups represented in the microbiome composition dataset, and phylogenetic distance between taxonomic groups represented in the microbiome composition dataset. 
     
     
         3 . The method of  claim 1 , further comprising: diagnosing the individual with chronic fatigue syndrome, upon generating an association between a sample processed from the individual and a set of taxonomic features and a set of functional features according to the characterization model. 
     
     
         4 . The method of  claim 3 , wherein the set of taxonomic features includes at least one of: a first taxonomic feature related to  Dorea  (genus) and a second taxonomic feature related to  Collinsella  (genus). 
     
     
         5 . The method of  claim 3 , wherein the set of taxonomic features includes at least one of: a third taxonomic feature related to Coriobacteriaceae (family) and a fourth taxonomic feature related to Actinobacteria (class). 
     
     
         6 . The method of  claim 3 , wherein the set of taxonomic features includes at least one of: a fifth taxonomic feature related to  Bifidobacterium  (genus), a sixth taxonomic feature related to Oscillospiraceae (family) and a seventh taxonomic feature related to Bifidobacteriaceae (family). 
     
     
         7 . The method of  claim 3 , wherein the set of taxonomic features includes at least one of: an eighth taxonomic feature related to Coriobacteriales (order) and a ninth taxonomic feature related to Bifidobacteriales (order). 
     
     
         8 . The method of  claim 3 , wherein the set of functional features includes at least one of: a first functional feature related to carbohydrate metabolism and a second functional feature related to ribosome biogenesis. 
     
     
         9 . The method of  claim 3 , wherein the set of functional features includes at least one of: a third functional feature related to pentose and glucuronate interconversions and a fourth functional feature related to peptidoglycan biosynthesis. 
     
     
         10 . The method of  claim 3 , wherein the set of functional features includes at least one of: a fifth functional feature related to metabolism. 
     
     
         11 . The method of  claim 10 , further comprising: at an output device associated with the individual and in communication with the computing system, promoting a therapy to the individual diagnosed with chronic fatigue syndrome, in accordance with the therapy model, wherein promoting the therapy comprises promoting a microbiome modifying therapy to the individual, the microbiome modifying therapy comprising a consumable configured to affect a taxonomic group associated with at least one of the set of taxonomic features and the set of functional features, in order to improve the health state the individual with chronic fatigue syndrome. 
     
     
         12 . A method for diagnosing and treating chronic fatigue syndrome, the method comprising:
 at a sample handling network, processing content of a sample from a subject, thereby generating a microbiome composition dataset and a microbiome functional feature dataset associated with the sample;   at a computing system in communication with the sample handling network, identifying an association between the sample and at least one of a taxonomic feature from the microbiome composition dataset and a functional feature from the microbiome functional feature dataset;   based upon the association, diagnosing the subject with chronic fatigue syndrome; and   delivering a therapy to the subject, wherein delivering the therapy comprises delivering a microbiome modifying therapy to the subject in order to improve a health state of the subject with chronic fatigue syndrome.   
     
     
         13 . The method of  claim 12 , wherein diagnosing the subject with chronic fatigue syndrome comprising identifying the association between the sample and at least one of: a set of taxonomic features from the microbiome composition dataset and a set of functional features from the microbiome functional feature dataset. 
     
     
         14 . The method of  claim 13 , wherein the set of taxonomic features includes at least a first taxonomic feature related to  Dorea  (genus) and wherein the set of functional features includes at least a first functional feature related to carbohydrate metabolism. 
     
     
         15 . The method of  claim 12 , wherein the set of taxonomic features includes at least a second taxonomic feature related to  Collinsella  (genus) and wherein the set of functional features includes at least a second functional feature related to ribosome biogenesis. 
     
     
         16 . The method of  claim 15 , wherein the set of taxonomic features includes at least a third taxonomic feature related to Coriobacteriaceae (family) and wherein the set of functional features includes at least a third functional feature related to pentose and glucuronate interconversions. 
     
     
         17 . The method of  claim 16 , wherein the set of taxonomic features includes at least a fourth taxonomic feature related to Actinobacteria (class) and wherein the set of functional features includes at least a fourth functional feature related to peptidoglycan biosynthesis. 
     
     
         18 . The method of  claim 12 , wherein the set of functional features includes at least one of: features derived from clusters of orthologous groups features, features derived from a Kyoto Encyclopedia of Genes and Genomes, and gene ontology features. 
     
     
         19 . The method of  claim 12 , wherein delivering the therapy comprises promoting at least one of a probiotic therapy and a prebiotic therapy to the subject, wherein the therapy comprises a consumable that selectively modulates at least one of: a population size of a desired taxon and a population size of a desired microbiome function, associated with improving the health state of the subject with chronic fatigue syndrome. 
     
     
         20 . A method for diagnosing and treating chronic fatigue syndrome, the method comprising:
 at a sample handling network, processing nucleic acid content of a sample from a subject, thereby generating a microbiome composition dataset associated with the sample;   at a computing system in communication with the sample handling network, identifying an association between the sample and a first taxonomic feature from the microbiome composition dataset wherein the first taxonomic feature is associated with at least one of  Dorea  (genus) and  Collinsella  (genus);   based upon the association, diagnosing the subject with chronic fatigue syndrome; and   delivering a therapy to the subject, wherein delivering the therapy comprises promoting a microbiome modifying therapy to the subject in order to improve a health state of the subject with chronic fatigue syndrome.   
     
     
         21 . The method of  claim 20 , wherein identifying the association further includes identifying the association between the sample and: a third taxonomic feature related to Coriobacteriaceae (family) and a first functional feature related to carbohydrate metabolism. 
     
     
         22 . The method of  claim 20 , wherein identifying the association further includes identifying the association between the sample and: a fourth taxonomic feature related to Actinobacteria (class) and a second functional feature related to ribosome biogenesis. 
     
     
         23 . The method of  claim 22 , wherein identifying the association further includes identifying the association between the sample and: a fifth taxonomic feature related to  Bifidobacterium  (genus), a sixth taxonomic feature related to Oscillospiraceae (family) and a seventh taxonomic feature related to Bifidobacteriaceae (family). 
     
     
         24 . The method of  claim 23 , wherein identifying the association further includes identifying the association between the sample and: an eighth taxonomic feature related to Coriobacteriales (order) and a ninth taxonomic feature related to Bifidobacteriales (order). 
     
     
         25 . The method of  claim 24 , wherein delivering the therapy comprises promoting at least one of a probiotic therapy and a prebiotic therapy to the subject, wherein the therapy comprises a consumable that selectively modulates a population size of a desired taxon associated with at least one of the first, second, and third taxonomic features and at least one of the first and second functional features. 
     
     
         26 . The method of  claim 25 , wherein delivering the therapy comprises promoting at least one of a probiotic therapy and a prebiotic therapy to the subject, wherein the therapy comprises a consumable that selectively modulates a population size of a desired taxon associated with at least one of the fourth, fifth, seventh, eighth and ninth taxonomic features.