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Tytuł pozycji:

Identification of Biomarkers of Impaired Sensory Profiles among Autistic Patients.

Tytuł :
Identification of Biomarkers of Impaired Sensory Profiles among Autistic Patients.
Autorzy :
El-Ansary A; Central Laboratory, Center for Female Scientific and Medical Colleges, King Saud University, Riyadh, Saudi Arabia.; Therapuetic Chemistry Department, National Research Centre, Dokki, Cairo, Egypt.
Hassan WM; Department of Biomedical Sciences, College of Health Sciences, University of Wisconsin - Milwaukee, Milwaukee, Wisconsin, United States of America.
Qasem H; Biochemistry Department, Science College, King Saud University, Riyadh, Saudi Arabia.
Das UN; UND Life Sciences, 2020 S 360th St, # K-202, Federal Way, Washington, 98003, United States of America.; BioScience Research Centre, GVP College of Engineering Campus, Visakhapatnam-530048, India.
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Źródło :
PloS one [PLoS One] 2016 Nov 08; Vol. 11 (11), pp. e0164153. Date of Electronic Publication: 2016 Nov 08 (Print Publication: 2016).
Typ publikacji :
Journal Article
Język :
Imprint Name(s) :
Original Publication: San Francisco, CA : Public Library of Science
MeSH Terms :
Autistic Disorder/*metabolism
Adolescent ; Child ; Child, Preschool ; Cognition Disorders/metabolism ; Cyclooxygenase 2/metabolism ; Dinoprost/analogs & derivatives ; Dinoprost/metabolism ; Dinoprostone/metabolism ; Female ; Humans ; Interleukin-10/metabolism ; Interleukin-12/metabolism ; MAP Kinase Kinase 1/metabolism ; Male ; NF-kappa B/metabolism ; Phosphatidylcholines/metabolism ; Phosphatidylserines/metabolism ; Phospholipases A2/metabolism ; Prostaglandin-E Synthases/metabolism
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Substance Nomenclature :
0 (Biomarkers)
0 (NF-kappa B)
0 (Phosphatidylcholines)
0 (Phosphatidylserines)
130068-27-8 (Interleukin-10)
187348-17-0 (Interleukin-12)
27415-26-5 (8-epi-prostaglandin F2alpha)
B7IN85G1HY (Dinoprost)
EC (Cyclooxygenase 2)
EC (MAP Kinase Kinase 1)
EC (Phospholipases A2)
EC (Prostaglandin-E Synthases)
K7Q1JQR04M (Dinoprostone)
Entry Date(s) :
Date Created: 20161109 Date Completed: 20170627 Latest Revision: 20181113
Update Code :
PubMed Central ID :
Czasopismo naukowe
Background: Autism is a neurodevelopmental disorder that displays significant heterogeneity. Comparison of subgroups within autism, and analyses of selected biomarkers as measure of the variation of the severity of autistic features such as cognitive dysfunction, social interaction impairment, and sensory abnormalities might help in understanding the pathophysiology of autism.
Methods and Participants: In this study, two sets of biomarkers were selected. The first included 7, while the second included 6 biomarkers. For set 1, data were collected from 35 autistic and 38 healthy control participants, while for set 2, data were collected from 29 out of the same 35 autistic and 16 additional healthy subjects. These markers were subjected to a principal components analysis using either covariance or correlation matrices. Moreover, libraries composed of participants categorized into units were constructed. The biomarkers used include, PE (phosphatidyl ethanolamine), PS (phosphatidyl serine), PC (phosphatidyl choline), MAP2K1 (Dual specificity mitogen-activated protein kinase kinase 1), IL-10 (interleukin-10), IL-12, NFκB (nuclear factor-κappa B); PGE2 (prostaglandin E2), PGE2-EP2, mPGES-1 (microsomal prostaglandin synthase E-1), cPLA2 (cytosolic phospholipase A2), 8-isoprostane, and COX-2 (cyclo-oxygenase-2).
Results: While none of the studied markers correlated with CARS and SRS as measure of cognitive and social impairments, six markers significantly correlated with sensory profiles of autistic patients. Multiple regression analysis identifies a combination of PGES, mPGES-1, and PE as best predictors of the degree of sensory profile impairment. Library identification resulted in 100% correct assignments of both autistic and control participants based on either set 1 or 2 biomarkers together with a satisfactory rate of assignments in case of sensory profile impairment using different sets of biomarkers.
Conclusion: The two selected sets of biomarkers were effective to separate autistic from healthy control subjects, demonstarting the possibility to accurately predict the severity of autism using the selected biomarkers. The effectiveness of the identified libraries lied in the fact that they were helpful in correctly assigning the study population as control or autistic patients and in classifying autistic patients with different degree of sensory profile impairment.

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