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

• US 10,346,592 B2
• Filed: 07/06/2016
• Issued: 07/09/2019
• Est. Priority Date: 10/21/2014
• Status: Active Grant

• Current Assignee: Psomagen, Inc.
• Original Assignee: uBiome, Inc.
• Inventors: Apte, Zachary, Almonacid, Daniel, Richman, Jessica, Behbahani, Siavosh Rezvan
• Primary Examiner(s): Dejong, Eric S
• Application Number:
  US15/203,589
• Publication Number:
  US 20160314281A1
• Time in Patent Office: 1,098 Days
• Field of Search: None
• CPC Class Codes: A61K 35/741 Probiotics probiotic yeast, e.g. saccharomyces A61K36/06
• CPC Class Codes: A61K 35/742 Spore-forming bacteria, e.g. Bacillus coagulans, Bacillus subtilis, clostridium or Lactobacillus sporogenes
• CPC Class Codes: A61K 35/744 Lactic acid bacteria, e.g. enterococci, pediococci, lactococci, streptococci or leuconostocs
• CPC Class Codes: A61K 35/745 Bifidobacteria
• CPC Class Codes: A61K 35/747 Lactobacilli, e.g. L. acidophilus or L. brevis
• CPC Class Codes: A61K 45/06 Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/10 Ontologies; Annotations
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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.

Claims

1. A method for diagnosing and treating an autism spectrum disorder in a subject, the method comprising:

at a sample handling network, processing nucleic acid content of a sample from the subject, thereby generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset associated with the sample;

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 diversity dataset, upon processing the sample from the subject;

based upon the association, diagnosing the subject with the autism spectrum disorder; and

providing a therapy to the subject associated with the autism spectrum disorder for facilitating improvement of a health state of the subject.

2. The method of claim 1, wherein diagnosing the subject with the autism spectrum disorder comprises identifying a first taxonomic feature associated with Anaerosporobacter (genus) in association with the sample.

3. The method of claim 2, wherein diagnosing the subject with the autism spectrum disorder comprises identifying a second taxonomic feature associated with Finegoldia (genus) in association with the sample.

4. The method of claim 3, wherein diagnosing the subject with the autism spectrum disorder comprises identifying a third taxonomic feature associated with Peptoniphilus (genus) in association with the sample.

5. The method of claim 4, wherein diagnosing the subject with the autism spectrum disorder comprises identifying a fourth taxonomic feature associated with Lactococcus (genus) in association with the sample.

6. The method of claim 5, wherein diagnosing the subject with the autism spectrum disorder comprises identifying a fifth taxonomic feature associated with Citrobacter (genus) in association with the sample.

7. The method of claim 1, wherein diagnosing the subject with the autism spectrum disorder comprises identifying at least one of a set of functional features derived from one or more of:

clusters of orthologous groups of proteins features, genomic functional features, chemical functional features, and systemic functional features.

8. The method of claim 1, wherein diagnosing the subject with the autism spectrum disorder comprises diagnosing the subject with Asperger'"'"'s syndrome, wherein diagnosing the subject comprises identifying at least one of a set of taxonomic features from:

a first taxonomic feature associated with Lactococcus (genus), a second taxonomic feature associated with Pseudoclavibacter (genus), a third taxonomic feature associated with Citrobacter (genus), and a fourth taxonomic feature associated with Microbacteriaceae (family) in association with the sample.

9. The method of claim 8, wherein diagnosing the subject with Asperger'"'"'s syndrome comprises identifying at least one of:

a fifth taxonomic feature associated with Fusobacterium (genus), a sixth taxonomic feature associated with Fusobacteriaceae (family), and a seventh taxonomic feature associated with Fusobacteriales (order) in association with the sample.

10. The method of claim 8, wherein diagnosing the subject with Asperger'"'"'s syndrome comprises identifying at least one of a set of functional features derived from one or more of:

clusters of orthologous groups of proteins features, genomic functional features, chemical functional features, and systemic functional features.

11. The method of claim 1, further comprising promoting a prebiotic therapy to the subject, wherein the prebiotic 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 correction of the autism spectrum disorder in the subject.

12. The method of claim 1, wherein providing the therapy comprises promoting a probiotic therapy to the subject, wherein the probiotic therapy comprises a consumable that affects at least one of:

a microorganism component of the subject, and a microbiome function in the subject, in promoting improvement of a state of the autism spectrum disorder in the subject.

13. The method of claim 1, wherein providing the therapy comprises promoting the therapy to the subject, wherein promoting the therapy comprises promoting a microbiome modifying therapy to the subject in order to improve a state of the autism spectrum disorder in the subject.

14. A method for characterizing an autism spectrum disorder in at least a subject, the method comprising:

at a sample handling network, receiving an aggregate set of samples from a population of subjects;

generating a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects upon processing nucleic acid content of each of the aggregate set of samples;

receiving a supplementary dataset, associated with at least a subset of the population of subjects, wherein the supplementary dataset is informative of characteristics associated with the autism spectrum disorder;

transforming the supplementary dataset and features extracted from the microbiome composition dataset and the microbiome functional diversity dataset into a characterization model of the autism spectrum disorder;

based upon the characterization model, generating a therapy model configured to improve a state of the autism spectrum disorder; and

providing a therapy to the subject associated with the autism spectrum disorder, based on the therapy model.

15. The method of claim 14, wherein processing nucleic acid content of each of the aggregate set of samples comprises processing with a fragmentation operation, a multiplexed amplification operation using a set of primers, a sequencing analysis operation, and an alignment operation.

16. The method of claim 14, 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 autism spectrum disorder and a second subset of the population of subjects not exhibiting the autism spectrum disorder.

17. The method of claim 14, further comprising:

diagnosing an individual with the autism spectrum disorder, according to the characterization model, upon identifying at least one of;

a set of taxonomic features, and a set of functional features, associated with a sample processed from the individual.

18. The method of claim 17, wherein diagnosing the individual comprises identifying a first taxonomic feature associated with Lactococcus (genus) and a second taxonomic feature associated with Citrobacter (genus) in association with the sample.

19. The method of claim 17, wherein providing the therapy comprises:

at an output device associated with the individual, promoting the therapy to the individual with the autism spectrum disorder, in accordance with the therapy model.

20. The method of claim 19, wherein promoting the therapy comprises promoting a microbiome-modifying therapy to the individual, the microbiome-modifying therapy configured to affect at least one of a Lactococcus population and a Citrobacter population in the individual, in order to improve the state of the autism spectrum disorder in the individual.