Metabolomic biomarkers in autism: identification of complex dysregulations of cellular bioenergetics

Frontiers in Psychiatry

Psychiatry

Denise M. Ney¹  David G. Amaral²  Marvin R. Natowicz³  Robert E. Burrier⁴  Elizabeth L. R. Donley⁴  Alan M. Smith⁴ 

[1] Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, United States;Department of Psychiatry and Behavioral Sciences, The MIND Institute, University of California, Davis, Davis, CA, United States;Pathology and Laboratory Medicine, Genomic Medicine, Neurological and Pediatrics Institutes, Cleveland Clinic, Cleveland, OH, United States;Stemina Biomarker Discovery, Inc, Madison, WI, United States;

关键词: autism;    pathophysiology;    bioenergetics;    subtypes;    biomarker;    metabolomic;    stratification;    mitochondria;   

DOI  :  10.3389/fpsyt.2023.1249578

 received in 2023-06-28, accepted in 2023-08-30,  发布年份 2023

来源: Frontiers

【 摘 要 】

Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case–control study of 499 autistic and 209 typically developing (TYP) children, ages 18–48 months, enrolled in the Children’s Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5–11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants’ biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.

【 授权许可】

Unknown   
Copyright © 2023 Smith, Donley, Ney, Amaral, Burrier and Natowicz.