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SAL_24766 details
Primary information
SALIDSAL_24766
Biomarker namehsa-miR-32-5p
Biomarker TypeDiagnostic
Sampling MethodThe sample size of 80 participants consisted of children with detected developmental delays/disorders (DD) (n = 55) and typically developing (TD) pre-school children with no previously detected developmental problems were classified as the control group (n = 25).
Collection MethodA total of 80 saliva samples were collected in a non-fasting state after rinsing with tap water with at least 30 minutes timespan from the last meal.
Analysis MethodqPCR
Collection SiteSaliva
Disease CategoryDevelopmental Disorder
Disease/ConditionDevelopmental Disorder
Disease SubtypeNA
Fold Change/ ConcentrationNA
Up/DownregulatedDownregulated
ExosomalNA
OrganismHomo sapiens
PMID32353026
Year of Publication2020
Biomarker IDhsa-miR-32-5p
Biomarker CategorymiRNA
SequenceUAUUGCACAUUACUAAGUUGCA
Title of studyIdentification of developmental disorders including autism spectrum disorder using salivary miRNAs in children from Bosnia and Herzegovina
Abstract of studyAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by major social, communication and behavioural challenges. The cause of ASD is still unclear and it is assumed that environmental, genetic and epigenetic factors influence the risk of ASD occurrence. MicroRNAs (miRNAs) are short 21-25 nucleotide long RNA molecules which post-transcriptionally regulate gene expression. MiRNAs play an important role in central nervous system development; therefore, dysregulation of miRNAs is connected to changes in behaviour and cognition observed in many disorders including ASD. Based on previously published work, on diagnosing ASD using miRNAs, we hypothesized that miRNAs can be used as biomarkers in children with suspected developmental disorders (DD) including ASD within Bosnian-Herzegovinian (B&H) population. 14 selected miRNAs were tested on saliva of children with suspected developmental disorders including ASD. The method of choice was qRT-PCR as a relatively cheap method available in most diagnostic laboratories in low to mid-income countries (LMIC). Out of 14 analysed miRNAs, 6 were differentially expressed between typically developing children and children with some type of developmental disorder including autism spectrum disorder. Using the most optimal logistic regression, we were able to distinguish between ASD and typically developing (TD) children. We have found 5 miRNAs as potential biomarkers. From those, 3 were differentially expressed within the ASD cohort. All 5 miRNAs had shown good chi-square statistics within the logistic regression performed on all 14 analysed miRNAs. The accuracy of 5-miRNAs model training set was 90.2%, while the validation set had a 90% accuracy. This study has shown that miRNAs may be considered as biomarkers for ASD detection and may be used to identify children with ASD along with standard developmental screening tests. By combining these methods we may be able to reach a reliable and accessible diagnostic model for children with ASD in LMIC such as B&H.