Blood biomarker discovery for autism spectrum disorder: A proteomic analysis
Laura Hewitson, Jeremy A. Mathews, Morgan Devlin, Claire Schutte, Jeon Lee, Dwight C. German
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 are 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.
Introduction
Autism spectrum disorder (ASD), a heterogeneous neurodevelopmental disorder, is characterized by deficits in social communication and social interaction, with restricted, repetitive patterns of behavior, interests, or activities [1]. ASD impacts at least 1 out of every 59 children in the U.S. [2], although this is likely underestimated [3]. Consequently, ASD is associated with considerable personal, family, and societal costs. For these reasons, efforts directed toward determining the underlying pathobiology of ASD, as well as ASD prevention, early diagnosis, and effective treatments, are public health priorities [4].
Materials and method
Participants
The study protocol and subsequent amendments were submitted by The Johnson Center for Child Health and Development (Austin, TX) and approved either by the Austin Multi-Institutional Review Board (for samples collected before October 2016) or IntegReview Institutional Review Board (for samples collected from October 2016 onwards). The study was carried out in accordance with the relevant guidelines and regulations.
Results
A total of 1,125 proteins identified using the SomaLogic SOMAScanTM platform were included in the analyses. Three computational methods were combined to search for a panel of proteins with high predictive power for ASD. The top-10 proteins were sought using RF analysis, t-test analysis between ASD and TD groups, and a correlation analysis with ASD severity (Fig 2). Six proteins were shared between RF and t-test prediction models used: mitogen-activated protein kinase 14 (MAPK14), immunoglobulin D (IgD), dermatopontin (DERM), ephrin type-B receptor 2 (EPHB2), soluble urokinase-type plasminogen activator receptor (suPAR), and calcineurin. These 6 proteins were defined as core proteins (Table 2).
Discussion
The goal of the present study was to identify a blood biomarker profile for ASD from >1,200 proteins using the SOMAScanTM platform. Twelve proteins were identified based upon a novel combination of machine learning methods with random forest analysis, t-test analysis, and correlation analysis with ADOS total scores that produced an accurate identification of ASD in boys. Six of the proteins, IgD, suPAR, MAPK14, EPHB2, DERM, and calcinerin were present in RF and t-test analyses and were considered core proteins in the panel.
Acknowledgments
We would like to thank all of the families that have participated in this research study. We would also like to acknowledge all of the staff at the Johnson Center for their ongoing support of our research program.
Citation: Hewitson L, Mathews JA, Devlin M, Schutte C, Lee J, German DC (2024) Blood biomarker discovery for autism spectrum disorder: A proteomic analysis. PLoS ONE 19(12): e0302951. https://doi.org/10.1371/journal.pone.0302951
Editor: Claudia Brogna, Fondazione Policlinico Universitario Gemelli IRCCS, ITALY
Received: April 27, 2024; Accepted: September 25, 2024; Published: December 19, 2024
Copyright: © 2024 Hewitson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: LH - Ted Lindsay Foundation, https://www.tedlindsay.org JL - Cancer Prevention and Research Institute (CPRIT) (RP150596), https://www.cprit.state.tx.us/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
