A machine learning approach for understanding the metabolomics response of children with autism spectrum disorder to medical cannabis treatment.

Autism spectrum disorder (ASD) is a neurodevelopmental condition impacting behavior, communication, social interaction and learning abilities. Medical cannabis (MC) treatment can reduce clinical symptoms in individuals with ASD. Cannabis-responsive biomarkers are metabolites found in saliva that change in response to MC treatment. Previously we showed levels of these biomarkers in children with ASD successfully treated with MC shift towards the physiological levels detected in typically developing (TD) children, and potentially can quantify the impact. Here, we tested for the first time the capabilities of machine learning techniques applied to our dynamic, high-resolution and rich feature dataset of cannabis-responsive biomarkers from a limited number of children with ASD before and after MC treatment and a TD group to identify: (1) biomarkers distinguishing ASD and TD groups; (2) non-cannabinoid plant molecules with synergistic effects; and (3) biomarkers associated with specific cannabinoids. We found: (1) lysophosphatidylethanolamine can distinguish between ASD and TD groups; (2) novel phytochemicals contribute to the therapeutic effects of MC treatment by inhibition of acetylcholinesterase; and (3) THC- and CBD-associated cannabis-responsive biomarkers are two distinct groups, while CBG is associated with some biomarkers from both groups.

The Potential of Salivary Lipid-Based Cannabis-Responsive Biomarkers to Evaluate Medical Cannabis Treatment in Children with Autism Spectrum Disorder.

Introduction: Autism spectrum disorder (ASD) is a group of heterogeneous neurodevelopmental conditions affecting social communication and social interaction. Medical cannabis (MC) treatment shows promising results as an approach to reduce behavioral difficulties, as determined mainly by subjective observations. We have recently shown the potential of cannabis-responsive biomarkers detected in saliva of children with ASD to objectively quantify the impact of successful MC treatment using a metabolomics approach. Since the pathology of ASD is associated with abnormal lipid metabolism, we used lipidomics on the same samples to (1) expand the repertoire of cannabis-responsive biomarkers and (2) provide preliminary insight into the role of MC on lipid metabolism. Materials and Methods: Saliva samples collected from children with ASD (n=15) treated with MC (both before and at the time of maximal impact of treatment) and an age-matched group of typically developing (TD) children (n=9) were subjected to untargeted lipidomics. The study was observational. Each child from the ASD group was receiving a unique individualized MC treatment regimen using off-the-shelf products as permitted by California law under physician supervision for at least 1 year. Doses of tetrahydrocannabinol (THC) ranged from 0.05 to 50 mg and cannabidiol (CBD) from 7.5 to 200 mg per treatment. The ASD group was evaluated for signs of improvement using parental brief Likert scale surveys. Results: Twenty-two potential lipid-based cannabis-responsive biomarkers exhibiting a shift toward the TD physiological levels in children with ASD after MC treatment were identified. Members from all five lipid subclasses known to be present in saliva were characterized. Preliminary lipid association network analysis suggests involvement of two subnetworks previously linked to (1) inflammation and/or redox regulation and (2) oxidative stress. The significant changes in sphingomyelin in this study and in N-acetyl-aspartate (NAA) previously detected in the metabolomics analysis of the same saliva samples may indicate a role of MC in neuron function. Conclusions: Our findings suggest that lipid metabolites in saliva can potentially serve as cannabis-responsive biomarkers and objectively quantify the impact of MC treatment, and indicate a possible mechanism of action for MC. This preliminary study requires further investigation with a larger population and appropriate clinical trial monitoring.

Cannabis-Responsive Biomarkers: A Pharmacometabolomics-Based Application to Evaluate the Impact of Medical Cannabis Treatment on Children with Autism Spectrum Disorder.

Introduction: Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions that impact behavior, communication, social interaction, and learning abilities. Treatment of ASD with medical cannabis (MC) shows promising results in reducing the severity of certain behavioral aspects. The goals of this observational study are to demonstrate the potential of metabolic biomarkers to (1) objectively determine the impact on metabolites of MC treatment and (2) suggest the metabolic pathways of children with ASD, who respond to MC treatment. Materials and Methods: The impact of effective physician-supervised MC treatment on children with ASD (n=15), compared with an age-matched group of typically developing (TD; n=9) children, was evaluated in an observational study design. Each child followed a unique MC regimen determined by their specific response over at least 1 year of treatment, which included the following: tetrahydrocannabinol-dominant MC (dosing range 0.05-50 mg per dose) in 40% of children and cannabidiol-dominant MC (dosing range 7.5-200 mg per dose) in 60% of children. Samples from the ASD group collected pre-MC treatment and at time of maximal impact, and from the TD group, were subjected to salivary metabolomics analysis. Ten minutes before saliva sampling, parents filled out behavioral rating surveys. Results: Sixty-five potential cannabis-responsive biomarkers exhibiting a shift toward the TD physiological levels were identified in children with ASD after MC treatment. For each biomarker, the physiological levels were determined based on the values detected in the TD group. A similar qualitative improvement trend in children with ASD treated with MC was also observed in the behavioral surveys. Twenty-three potential Cannabis-Responsive biomarkers exhibiting change toward TD mean were categorized as anti-inflammatory, bioenergy associated, neurotransmitters, amino acids, and endocannabinoids. The changes in the levels of the Cannabis-Responsive biomarkers N-acetylaspartic acid, spermine, and dehydroisoandrosterone 3-sulfate have been previously linked to behavioral symptoms commonly observed in individuals with ASD. Conclusions: Our results suggest Cannabis-Responsive biomarkers shift toward the TD mean after MC treatment and can potentially quantify benefit at the metabolic level. These changes appear to be similar to the trend described in behavior surveys. Larger trials are needed to confirm these preliminary findings.

"My two-week-old daughter is throwing up blood".

Swallowed maternal blood at the time of delivery or from cracked nipples during breastfeeding is the most common cause of suspected gastrointestinal bleeding in the neonate. In this case, the Apt-Downey test is a useful diagnostic tool. The Apt-Downey test can effectively differentiate neonatal from maternal hemoglobin based on the conversion of oxyhemoglobin to alkaline globin hematin when mixed with alkali.