A Potential Biomarker of Brain Activity in Autism Spectrum Disorders: A Pilot fNIRS Study in Female Preschoolers

Autism spectrum disorder (ASD) refers to a neurodevelopmental condition whose detection still remains challenging in young females due to the heterogeneity of the behavioral phenotype and the capacity of camouflage. The availability of quantitative biomarkers to assess brain function may support in the assessment of ASD. Functional Near-infrared Spectroscopy (fNIRS) is a non-invasive and flexible tool that quantifies cortical hemodynamic responses (HDR) that can be easily employed to describe brain activity. Since the study of the visual phenotype is a paradigmatic model to evaluate cerebral processing in many neurodevelopmental conditions, we hypothesized that visually-evoked HDR (vHDR) might represent a potential biomarker in ASD females. We performed a case-control study comparing vHDR in a cohort of high-functioning preschooler females with ASD (fASD) and sex/age matched peers. We demonstrated the feasibility of visual fNIRS measurements in fASD, and the possibility to discriminate between fASD and typical subjects using different signal features, such as the amplitude and lateralization of vHDR. Moreover, the level of response lateralization was correlated to the severity of autistic traits. These results corroborate the cruciality of sensory symptoms in ASD, paving the way for the validation of the fNIRS analytical tool for diagnosis and treatment outcome monitoring in the ASD population.

Automated summary

Autism spectrum disorder (ASD) is a challenging neurodevelopmental condition to detect in young females due to the heterogeneity of the behavioral phenotype and the capacity of camouflage. Functional Near-infrared Spectroscopy (fNIRS) is a non-invasive tool that can quantify cortical hemodynamic responses (HDR) and potentially serve as a biomarker for ASD in females. A case-control study on high-functioning preschooler females with ASD demonstrated the feasibility of using visual fNIRS measurements to discriminate between ASD and typical subjects based on signal features such as vHDR amplitude and lateralization. The level of response lateralization was also found to be correlated with the severity of autistic traits, highlighting the importance of sensory symptoms in ASD.