Autism-Open Access
Open Access

Brain Metabolic Disturbances in Autism Spectrum Disorder: A systematic Review

Hyuan-seok Kim

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Keywords: Autism spectrum disorder; brain imaging; Brain Metabolic Disturbances; neurodevelopmental process; Autism

Introduction

Autism Spectrum Disorder (ASD) is a difficult condition to understand. It encompasses a wide range of complex neurodevelopment disorders marked by repeated patterns of actions as well as problems with social connection and interaction. The changes in the brain are small, and we usually see them in aggregate over a large number of people because normal variations between people are far more drastic than the subtle systematic changes associated with autism [1]. Early-onset impairments of social communication and social interaction characterize Autism spectrum disorder (ASD), which is a chronic neurodevelopmental condition. ASD is a complex collection of diseases with varying degrees of functioning and comorbidity. This diversity makes accurate diagnosis difficult, particularly in preverbal children, and it has a high genetic heritability with complex inheritance patterns. Furthermore, many forms of 'idiopathic' ASD have no established genetic cause and are most likely influenced by environmental factors. The neurobiological investigation of  ASD is complicated by the disorder's heterogeneous roots. As a result, a well-controlled analysis in an etiologically homogeneous ASD model would aid in reducing the difficulty.

Brain Structures in ASD

Magnetic Resonance Image (MRI) studies have provided many implications of neurodevelopmental characteristics underlying ASD because neuroimaging is one of the few approaches that allow direct observation of the brain in vivo. While structural MRI (sMRI) studies have yielded a variety of findings over the last decade, there are grey and white matter abnormalities as well as regional brain differences between ASD and typically developing (TD) controls. In order to investigate atypical brain anatomy and neurodevelopment in ASD, several sMRI studies have investigated volumetric and morphometric brain. Reviewing these results sheds light on the neural substrates that underpin autism symptoms over the lifespan [2].

Brain Functions in ASD

Functional MRI (fMRI) and magnetoencephalography (MEG) are two neuroimaging techniques that can be used to investigate atypical brain functions in people with ASD. Many studies have shown that the structural differences between ASD and TD change with age. Since structural variations are linked to various functions of the brain domain, it's important to track brain functions over time. We will review recent research about the atypical brain functions of ASD based on two key features in age-dependent mannequins, according to the DSM-5 diagnostic criteria, social communication impairments and limited, repeated patterns of behaviours.

Brain Connectivity in ASD

The brain is a structural and functional structure with dynamic network characteristics. Early brain imaging research focused on region-specific differences in behaviour; however, accumulating evidence suggests that brain network activity plays an important role in brain function. Functional and structural connectivity are two types of brain connectivity: Brain activity has temporal parallels. A number of studies have found abnormal brain connectivity in people with ASD using brain imaging techniques including fMRI and diffusion tensor imaging (DTI). Many researchers have generally accepted the long-range cortical hypo-connectivity hypothesis, despite some contradictory reports that suggest hyper-connectivity in ASD. The Research Domain Criteria (RDoC) project was started by the National Institute of Mental Health in the United States to address the issue that a diagnosis based on symptoms does not necessarily lead to successful therapy. This project aimed to establish a framework for pathophysiology research, especially in the fields of neuroscience and genomics. Imaging studies can help to explain the underlying neuronal mechanisms of psychiatric disorders, resulting in new classification frameworks. This could lead to the development of therapeutic strategies that take into account the underlying pathophysiology [3,4]. These experiments are paving the way for the advancement of noninvasive, brain-based screening approaches that could theoretically detect variations prior to behavioural emergence, which would be a significant scientific advance. Cross-disciplinary developments have led to the advancement of innovative techniques for early diagnosis and more successful therapies for people with ASD, as well as a "more positive outcome" for those with the disorder. Since the protective factors are still unknown, ethical concerns about application and clinical guidelines based on biomarker measures must be carefully considered [5].

CONCLUSION

Despite the fact that there is a lot of evidence for anomalies in the ASD brain, the findings from various groups are contradictory. One of the reasons for the discrepancies is that researchers failed to account for developmental changes in the brains. Alternatively, defining more homogeneous ASD subgroups may be a viable approach. Age, gender, intellectual capacity, genetic factor, and environmental risk factor all play a role in ASD individual heterogeneity. More reliable evidence and a better understanding of the neurobiological causes of ASD would come from studies on these affective factors.

References

1. https://www.psycom.net/autism-brain-differences
2. Mizuno Y, Kagitani-Shimono K, Jung M, Makita K, Takiguchi S, Fujisawa TX, et al. Structural brain abnormalities in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder. Transl Psychiatry. 2019;9(1):1-7.
3. Ha S, Sohn IJ, Kim N, Sim HJ, Cheon KA. Characteristics of brains in autism spectrum disorder: structure, function and connectivity across the lifespan. Exp Neurobiol. 2015;24(4):273.
4. Cho H, Kim CH, Knight EQ, Oh HW, Park B, Kim DG, et al. Changes in brain metabolic connectivity underlie autistic-like social deficits in a rat model of autism spectrum disorder. Sci Rep. 2017;7(1):1-6.
5. Allely CS, Gillberg C, Wilson P. Neurobiological abnormalities in the first few years of life in individuals later diagnosed with autism spectrum disorder: a review of recent data. Behav Neurol. 2014.

References

1. Mizuno Y, Kagitani-Shimono K, Jung M, Makita K, Takiguchi S, Fujisawa TX, et al. Structural brain abnormalities in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder. Transl Psychiatry. 2019;9(1):1-7.
2. Ha S, Sohn IJ, Kim N, Sim HJ, Cheon KA. Characteristics of brains in autism spectrum disorder: structure, function and connectivity across the lifespan. Exp Neurobiol. 2015;24(4):273.
3. Cho H, Kim CH, Knight EQ, Oh HW, Park B, Kim DG, et al. Changes in brain metabolic connectivity underlie autistic-like social deficits in a rat model of autism spectrum disorder. Sci Rep. 2017;7(1):1-6.
4. Allely CS, Gillberg C, Wilson P. Neurobiological abnormalities in the first few years of life in individuals later diagnosed with autism spectrum disorder: a review of recent data. Behav Neurol. 2014.