Blood biomarker discovery for autism spectrum disorder: A proteomic analysis

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. A wide range of putative biological markers for ASD is currently being investigated. Proteomic analyses indicate that the levels of many proteins in plasma/serum are altered in ASD, suggesting that a panel of proteins may provide a blood biomarker for ASD. Serum samples from 76 boys with ASD and 78 typically developing (TD) boys, 18 months-8 years of age, were analyzed to identify possible early biological markers for ASD. Proteomic analysis of serum was performed using SomaLogic's SOMAScanTM assay 1.3K platform. A total of 1,125 proteins were analyzed. There were 86 downregulated proteins and 52 upregulated proteins in ASD (FDR < 0.05). Combining three different algorithms, we found a panel of 9 proteins that identified ASD with an area under the curve (AUC) = 0.8599±0.0640, with specificity and sensitivity of 0.8217±0.1178 and 0.835±0.1176, respectively. All 9 proteins were significantly different in ASD compared with TD boys, and were significantly correlated with ASD severity as measured by ADOS total scores. Using machine learning methods, a panel of serum proteins was identified that may be useful as a blood biomarker for ASD in boys. Further verification of the protein biomarker panel with independent test sets is warranted.

Fig 1. Range of ADOS scores among the ASD boys.

Each dot represents the ADOS total score for a single subject.

Fig 2. Top-10 predictive proteins identified by three different methods.

(A) Random Forest-based method. (B) T-test based method. A volcano plot of group comparison revealed a total of 86 proteins were downregulated in the ASD boys and 52 proteins were upregulated. All of these proteins had a false discovery rate <0.05. (C) Correlation-based method.

Fig 3. Optimization of the predictive proteins.

(A) Identification of the 5 core proteins. The core proteins were among the top-10 proteins identified by each of the 3 methods. (B) Identification of proteins with additive predictive power when combined with the core proteins (red asterisks). (C) Predictive power (AUC) of the top-10 proteins from the three different methods: RF–random forest, Ttest–t-tests, and Corr–correlation compared with the optimal panel of 9 proteins (AUC_Optimal) representing the 5 core proteins and the 4 additional proteins identified in Fig 3B).