Method and system for microbiome-derived diagnostics and therapeutics for autoimmune system conditions

Patent metadata

Field	Value
Publication number	US-10073952-B2
Application number	US-201615098027-A
Country	US
Kind code	B2
Filing date	Apr 13, 2016
Priority date	Oct 21, 2014
Publication date	Sep 11, 2018
Grant date	Sep 11, 2018

Abstract

A method for at least one of characterizing, diagnosing, and treating an autoimmune disorder 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 autoimmune condition 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 autoimmune condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

First claim

We claim:

1. A method for at least one of characterizing, diagnosing, and treating an autoimmune condition in at least a subject, the method comprising:
for each of an aggregate set of samples from a population of subjects:
determining a microorganism nucleic acid sequence, comprising:
identifying primers for nucleic acid sequences associated with the autoimmune condition,
fragmenting nucleic acid material from the sample, and amplifying the fragmented nucleic acid material using the identified primers; and

determining an alignment of the microorganism nucleic acid sequence to a reference nucleic acid sequence associated with the autoimmune condition;

generating a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects based on the;
receiving a supplementary dataset, associated with the population of subjects, wherein the supplementary dataset is informative of characteristics associated with the autoimmune condition;
transforming the supplementary dataset and features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset into a characterization model of the autoimmune condition;
based upon the characterization model, generating a therapy model configured to improve a state of the autoimmune condition; and
at an output device associated with the subject providing a therapy to the subject with the autoimmune condition, based upon processing a sample from the subject with the characterization model and the therapy model, wherein the therapy modulates microbiome composition to improve a state of the autoimmune condition.

2. The method of claim 1 , wherein generating the characterization model comprises performing a statistical analysis to assess a set of microbiome composition features and microbiome functional features having variations across a first subset of the population of subjects exhibiting the autoimmune condition and a second subset of the population of subjects not exhibiting the autoimmune condition.

3. The method of claim 2 , wherein generating the characterization model comprises:
extracting candidate features associated with a set of functional aspects of microbiome components indicated in the microbiome composition dataset to generate the microbiome functional diversity dataset; and
characterizing the autoimmune condition in association with a subset of the set of functional aspects, the subset derived from at least one of clusters of orthologous groups of proteins features, genomic functional features from the Kyoto Encyclopedia of Genes and Genomes (KEGG), genomic functional features from a Cluster of Orthologous Groups (COG) database, chemical functional features, and systemic functional features.

4. The method of claim 2 , wherein generating the characterization model of the autoimmune condition comprises generating a characterization that is diagnostic of at least one of: asthma, Sprue, acquired immune deficiency syndrome (AIDS), and multiple sclerosis (MS).

5. The method of claim 4 , wherein generating the characterization that is diagnostic of asthma comprises generating the characterization upon processing the aggregate set of samples and determining presence of features derived from 1) a set of taxa including: Filifactor (genus), Mycoplasma (genus), Mycoplasmataceae (family), and Mycoplasmatales (order).

6. The method of claim 4 , wherein generating the characterization that is diagnostic of Sprue comprises generating the characterization upon processing the aggregate set of samples and determining presence of features derived from 1) a set of taxa including: Bifidobacterium (genus), Bifidobacteriaceae (family), Bifidobacteriales (order), and Actinobacteria (class), and 2) a set of functions associated with a first Kyoto Encyclopedia of Genes and Genomes (KEGG) functional feature related to carbohydrate metabolism, a second KEGG functional feature related to ribosome biogenesis, and a third KEGG functional feature related to peptidoglycan biosynthesis.

7. The method of claim 4 , wherein generating the characterization that is diagnostic of multiple sclerosis comprises generating the characterization upon processing the aggregate set of samples and determining presence of features derived from 1) a set of taxa including Lactococcus (genus).

8. The method of claim 4 , wherein generating the characterization that is diagnostic of AIDS comprises generating the characterization upon processing the aggregate set of samples and determining presence of features derived from a set of functions associated with a first Kyoto Encyclopedia of Genes and Genomes (KEGG) functional feature related to neurodegenerative diseases, a second KEGG functional feature related to transcription, and a third KEGG functional feature related to glycolysis/gluconeogenesis.

9. The method of claim 2 , wherein generating the characterization model of the autoimmune condition comprises generating a characterization that is diagnostic of at least one of: rheumatoid arthritis, Sjogren's syndrome, Type I diabetes, and systemic lupus erythmatosus.

10. A method for diagnosing and treating an autoimmune condition in a subject, the method comprising:
for each of an aggregate set of samples from a population of subjects:
determining a microorganism nucleic acid sequence, comprising:
identifying primers for nucleic acid sequences associated with the autoimmune condition,
fragmenting nucleic acid material from the sample, and amplifying the fragmented nucleic acid material using the identified primers; and

determining an alignment of the microorganism nucleic acid sequence to a reference nucleic acid sequence associated with the autoimmune condition;

generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects based on the alignments, the microbiome functional diversity dataset indicative of systemic functions present in microbiome components of the aggregate set of samples;
transforming features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset into a characterization model of the autoimmune condition, wherein the characterization model is diagnostic of at least one of Sprue, asthma, and multiple sclerosis;
generating a therapy model, from the characterization model, configured to improve a state of the autoimmune condition; and
at an output device associated with the subject, providing a therapy to the subject having the autoimmune condition as determined using the therapy model, wherein the therapy modulates microbiome composition to improve a state of the autoimmune condition.

11. The method of claim 10 , wherein generating the characterization comprises performing a statistical analysis with at least one of the followings tests: a Kolmogorov-Smirnov test, a Welch t-test, a KS-test and a lognormal test to assess a set of microbiome composition features and microbiome functional features having varying degrees of abundance in a first subset of the population of subjects exhibiting the autoimmune condition and a second subset of the population of subjects not exhibiting the autoimmune condition.

12. The method of claim 11 , wherein generating the characterization model comprises analyzing a set of features from the microbiome composition dataset with the statistical analysis, wherein the set of features includes features associated with: relative abundance of different taxonomic groups represented in the microbiome composition dataset and phylogenetic distance between taxonomic groups represented in the microbiome composition

Assignees

• Ubiome Inc

Inventors

• Apte Zachary
• Almonacid Daniel
• Richman Jessica
• Behbahani Siavosh Rezvan

Classifications

• G06F19/28

  Physics · mapped topic

• G06F19/3418

  Physics · mapped topic

• Y02A90/26

  Cross-Sectional Technologies · mapped topic

• G06F19/24

  Physics · mapped topic

• G16H50/20 Primary

  for computer-aided diagnosis, e.g. based on medical expert systems · CPC title