Microbial signatures of autism spectrum disorder
AssigneePiton Therapeutics, Inc.
InventorsRobert Hardie Mills, Eric Hou-Jen Wang, Aries Chavira
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Abstract
Aspects of the disclosure relate to methods and compositions for diagnosing and/or treating subjects having one or more symptoms of Autism Spectrum Disorder (ASD) or subjects at risk of developing ASD. In some embodiments, methods comprise determining and/or modulating levels of chorismate and/or a molecule within a chorismate metabolic pathway in a subject. In some embodiments, methods comprise determining and/or modulating levels of a microbial feature (e.g., a Sarcina bacterium) in a subject. In some embodiments, methods comprise determining and/or modulating levels of proton flux in a gastrointestinal tract in a subject.
Claims59
A method of assisting in the diagnosis of a subject having one or more symptoms of autism, the method comprising determining a level of chorismate and/or a molecule within a chorismate metabolic pathway in a sample obtained from the subject.
A method of treating a subject having one or more symptoms of ASD or at risk of developing ASD, the method comprising modulating a level of chorismate and/or a molecule within a chorismate metabolic pathway in the subject.
A method comprising determining an abundance of one or more microbial features in a sample obtained from a subject to predict and/or diagnose an ASD status of the subject.
A method of assisting in the diagnosis of a subject having one or more symptoms of autism, the method comprising determining a level of proton influx in a gastrointestinal tract of the subject from a sample obtained from the subject.
A method for identifying a subtype of a subject with ASD, the method comprising determining a composition of fecal microbiome or a presence of one or more microbial features in a sample obtained from the subject.
A method comprising determining one or more microbial features in a sample obtained from a subject and using the one or more microbial features as biomarkers for medical decision making regarding therapeutic interventions.
A method comprising training a machine learning model to associate microbial features with a risk or risk level of ASD and/or with candidacy or non-candidacy for a treatment for ASD in a subject.
A non-transitory computer-readable storage medium having encoded thereon executable instructions that, when executed by at least one processor, cause the at least one processor to perform any one or any combination of the foregoing methods.
An apparatus comprising at least one processor and at least one non-transitory computer-readable storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to perform any one or any combination of the foregoing methods.
A method, comprising:
- determining an abundance of one or more molecules or microbial features in a sample obtained from a subject;
- and
- administering one or more therapies based on the absence and/or low abundance of the one or more molecules or microbial features to alleviate one or more symptoms of ASD and/or comorbidities of ASD or to reduce the risk of developing ASD.
A method comprising administering one or more probiotics and/or prebiotics based on the absence and/or low abundance of one or more microbial features to alleviate autistic comorbidities and phenotypes.
A method comprising targeting one or more microbial features based on the presence and/or excess of one or more microbial features to alleviate one or more symptoms of ASD and/or of comorbidities of ASD in a subject or to reduce the subject's risk of developing ASD.
The method of claim 56, wherein targeting the one or more microbial features comprises administering one or more antibiotics and/or phage therapy to the subject.
A method comprising targeting one or more microbial molecules associated with one or more microbial features to alleviate one or more symptoms of ASD and/or of comorbidities of ASD in a subject.
Dependencies are inferred from the claim text.