Abstract: A method for evaluating or monitoring metabolic effects of exercise or injury by detecting and/or quantifying microR-NAs in saliva. Compositions and methods of treatment based on detection of microRNAs.

Abstract: Provided are methods for detecting or diagnosing a traumatic brain injury or TBI by detecting concentration levels miRNAs associated with TBI in saliva. Methods for controlled and normalized comparisons of salivary miRNA concentration levels are further provided. Assay kits comprising salivary miRNAs, probes and/or primers for detecting salivary miRNAs are also provided.

Abstract: A method and composition for detecting, diagnosing, prognosing or monitoring a subject suspected of having or having Parkinson's disease by detecting miRNAs and microbial RNAs in saliva.

Abstract: This application provides methods to differentiate between subjects with autism spectrum disorder (ASD) and typically developing (TD) or developmentally delayed (DD) subjects using miRNA and/or microbiome levels detected in saliva samples and patient information. The method can be used to monitor the progress of ASD and guide its treatment. RNA-seq, qPCR, or other methods determine counts and abundance of miRNA or microbiomes. MicroRNA and/or microbiome sequencing data are refined by normalization to expression levels or abundance of time-invariant miRNAs and/or microbial RN As to control for time of sample collection or to compensate for circadian fluctuations in these levels. Multivariate logistic regression and nonlinear classification techniques are further used to select a panel of miRNAs and microbiomes that accurately differentiate between subjects with ASD, DD, and TD in subjects with an unknown ASD status. These panels of miRNAs and microbiomes may be developed into a RNA assay kit.

Abstract: A machine learning classifier that diagnoses autism spectrum disorder (ASD) is described that transforms data obtained from a patient medical history and a patients saliva into data that correspond to a test panel of features, the data for the features including human microtranscriptome and microbial transcriptome data, wherein the transcriptome data are associated with respective RNA categories for ASD. The classifier classifies the transformed data by applying the data to the classifier that has been trained to detect ASD using training data associated with the features of the test panel. The trained classifier includes vectors that define a classification boundary and predicts a probability of ASD based on results of the classifying.

Abstract: A method for detecting a risk of, diagnosing, prognosing, or monitoring anorexia nervosa or another eating disorder or for distinguishing a healthy subject from one with anorexia, an eating disorder, or an anxiety disorder comprising detecting at least one abnormal or altered pattern of miRNA and/or microbial RNA in biological sample compared to a control value from one or more normal subjects or healthy controls, and selecting a subject having at least one abnormal or altered pattern of miRNA and/or microbial RNA correlated with anorexia nervosa or another eating disorder. Probe and/or primer compositions for identifying miRNAs or microbial RNAs; compositions containing miRNAs or microbial RNAs, their mimics or agents that target miRNAs or microbial RNAs; and methods of treatment for AN and other eating disorders.

Abstract: A method for evaluating or monitoring metabolic effects of exercise or injury by detecting and/or quantifying microR-NAs in saliva. Compositions and methods of treatment based on detection of microRNAs.

Abstract: Provided are methods for detecting or diagnosing a traumatic brain injury or TBI by detecting concentration levels miRNAs associated with TBI in saliva. Methods for controlled and normalized comparisons of salivary miRNA concentration levels are further provided. Assay kits comprising salivary miRNAs, probes and/or primers for detecting salivary miRNAs are also provided.

Abstract: Methods for diagnosing or monitoring a condition, disorder or disease associated with circadian, diurnal or other temporal rhythms by detecting circa-miRNAs and circa-microbiomes associated with said condition, disorder or disease. Methods for correcting or normalizing sequence data to correct for diurnal or circadian fluctuations in quantities of circa-miRNAs and/or circa-microbiomes by adjusting or normalizing values based on the time of day when a saliva sample containing these RNAs was collected.

Abstract: This application provides methods to differentiate between subjects with autism spectrum disorder (ASD) and typically developing (TD) or developmentally delayed (DD) subjects using miRNA and/or microbiome levels detected in saliva samples and patient information. The method can be used to monitor the progress of ASD and guide its treatment. RNA-seq, qPCR, or other methods determine counts and abundance of miRNA or microbiomes. MicroRNA and/or microbiome sequencing data are refined by normalization to expression levels or abundance of time-invariant miRNAs and/or microbial RN As to control for time of sample collection or to compensate for circadian fluctuations in these levels. Multivariate logistic regression and nonlinear classification techniques are further used to select a panel of miRNAs and microbiomes that accurately differentiate between subjects with ASD, DD, and TD in subjects with an unknown ASD status. These panels of miRNAs and microbiomes may be developed into a RNA assay kit.