Pre-autism: What a paediatrician should know about early diagnosis of autism‎

Abstract

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as “pre-autism” when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

Metabolomic changes in children with autism

“…These differences can affect various metabolic pathways, including amino acid, energy, and neurotransmitter metabolism. By understanding the underlying metabolic mechanisms, researchers may be able to identify reliable biomarkers for early diagnosis of ASD, especially for at-risk populations[ 17 ]. Furthermore, understanding these metabolic discrepancies can open up avenues for highlighting how genetic predispositions and environmental factors interact to shape the metabolic profiles associated with ASD[ 32 ].…”

“…Integrating metabolomic data with other omics data (genomics, transcriptomics, proteomics) and clinical information can provide a more comprehensive view of the disorder and potentially lead to identifying biomarkers for early diagnosis, subtyping, and personalized interventions[ 16 ]. Metabolic changes that occur early in life could help in the early detection of autism in a clinical-stage called pre-autism[ 17 ]. This systematic review aims to discuss the various metabolomic changes that can affect the degree of autism and help in diagnosis and management.…”