Using machine learning, researchers have identified several patterns of maternal autoantibodies highly associated with the diagnosis and severity of autism.
Autism spectrum disorder (ASD) is characterised by social and behavioural impairment, along with restricted interests and repetitive behaviours. The incidence of ASD is rising. In fact, in 2018, 1 in 59 children in the USA were affected, making ASD an important health concern and a substantial socioeconomic burden.
Using western blot, earlier studies have identified autoantibody reactivity against seven proteins highly expressed in the developing brain. These specifically include CRMP1, CRMP2, GDA, LDHA, LDHB, STIP1 and YBOX. More recently, NSE was discovered as an additional target autoantigen. Autoantibody epitope mapping for these eight antigens has found peptide sequences only within maternal samples from a particular ASD group. This subtype of ASD is known as Maternal Autoantibody-Related (MAR) autism.
In this recent study, published in Molecular Psychiatry, researchers created a serological assay to identify ASD-specific maternal autoantibody patterns against the eight previously identified proteins. The team wanted to determine the relationship of these reactivity patterns with ASD outcome severity.
They utilised plasma from mothers of children diagnosed with ASD (n=450) and from typically developing children (n=342). They then used a machine-learning algorithm to determine which autoantibody patterns were specifically associated with a diagnosis of ASD.
The machine-learning algorithm identified three top patterns associated with MAR ASD: CRMP1+GDA, CRMP1+CRMP2 and NSE+STIP. They also found that reactivity to CRMP1 in the top patterns significantly increased the odds of a child having more severe autism.
These maternal biomarkers could be used for early diagnosis of MAR autism, which would enable implementation of more effective behavioural interventions. It also opens the door for more research on potential pre-conception testing for high-risk women.
Judy Van de Water, lead author, stated:
“We can envision that a woman could have a blood test for these antibodies prior to getting pregnant. If she had them, she’d know she would be at very high risk of having a child with autism. If not, she has a 43% lower chance of having a child with autism as MAR autism is ruled out.”
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