Preliminary evaluation of a novel nine-biomarker profile for the prediction of autism spectrum disorder

Autoři: Afaf El-Ansary aff001;  Wail M. Hassan aff004;  Maha Daghestani aff001;  Laila Al-Ayadhi aff003;  Abir Ben Bacha aff007
Působiště autorů: Central Laboratory, Center for Female Scientific and Medical Colleges, King Saud University, Riyadh, Saudi Arabia aff001;  Therapeutic Chemistry Department, National Research Centre, Dokki, Cairo, Egypt aff002;  Autism Research and Treatment Center, King Saud University, Riyadh, Saudi Arabia aff003;  Department of Biomedical Sciences, University of Missouri- Kansas City School of Medicine, Missouri, United States of America aff004;  Zoology Department, Science College, King Saud University, Riyadh, Saudi Arabia aff005;  Department of Physiology, Faculty of Medicine, King Saud University, Riyadh, Saudi Arabia aff006;  Biochemistry Department, Science College, King Saud University, Riyadh, Saudi Arabia aff007;  Laboratory of Plant Biotechnology Applied to Crop Improvement, Faculty of Science of Sfax, University of Sfax, Tunisia aff008
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227626



Autism spectrum disorder (ASD) is a complex group of heterogeneous neurodevelopmental disorders the prevalence of which has been in the rise in the past decade. In an attempt to better target the basic causes of ASD for diagnosis and treatment, efforts to identify reliable biomarkers related to the body’s metabolism are increasing. Despite an increase in identifying biomarkers in ASD, there are none so far with enough evidence to be used in routine clinical examination, unless medical illness is suspected. Promising biomarkers include those of mitochondrial dysfunction, oxidative stress, energy metabolism, and apoptosis.

Methods and participants

Sodium (Na+), Potassium (K+), glutathione (GSH), glutathione-s-transferase (GST), Creatine kinase (CK), lactate dehydrogenase (LDH), Coenzyme Q10, and melatonin (MLTN) were evaluated in 13 participants with ASD and 24 age-matched healthy controls. Additionally, five ratios, which include Na+/K+, GSH:GST, CK:Cas7, CoQ10: Cas 7, and Cas7:MLTN, were tested to measure their predictive values in discriminating between autistic individuals and controls. These markers, either in absolute values, as five ratios, or combined (9 markers + 5 ratios) were subjected to a principal component analysis and multidimensional scaling (MDS), and hierarchical clustering, which are helpful statistical tools in the field of biomarkers.


Our data demonstrated that both PCA and MDS analysis were effective in separating autistic from control subjects completely. This was also confirmed through the use of hierarchical clustering, which showed complete separation of the autistic and control groups based on nine biomarkers, five biomarker ratios, or a combined profile. Excellent predictive value of the measured profile was obtained using the receiver operating characteristics analysis, which showed an area under the curve of 1.


The availability of an improved predictive profile, represented by nine biomarkers plus the five ratios, inter-related different etiological mechanisms in ASD and would be valuable in providing greater recognition of the altered biological pathways in ASD. Our predictive profile could be used for the diagnosis and intervention of ASD.

Klíčová slova:

Autism – Autism spectrum disorder – Biomarkers – Glutathione – Glutathione chromatography – Melatonin – Mitochondria – Principal component analysis


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