A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years

Abstract

Autism Spectrum Disorder (ASD) diagnosis remains behavior-based and the median age of diagnosis is ~52 months, nearly 5 years after its first-trimester origin. Accurate and clinically-translatable early-age diagnostics do not exist due to ASD genetic and clinical heterogeneity. Here we collected clinical, diagnostic, and leukocyte RNA data from 240 ASD and typically developing (TD) toddlers (175 toddlers for training and 65 for test). To identify gene expression ASD diagnostic classifiers, we developed 42,840 models composed of 3570 gene expression feature selection sets and 12 classification methods. We found that 742 models had AUC-ROC ≥ 0.8 on both Training and Test sets. Weighted Bayesian model averaging of these 742 models yielded an ensemble classifier model with accurate performance in Training and Test gene expression datasets with ASD diagnostic classification AUC-ROC scores of 85–89% and AUC-PR scores of 84–92%. ASD toddlers with ensemble scores above and below the overall ASD ensemble mean of 0.723 (on a scale of 0 to 1) had similar diagnostic and psychometric scores, but those below this ASD ensemble mean had more prenatal risk events than TD toddlers. Ensemble model feature genes were involved in cell cycle, inflammation/immune response, transcriptional gene regulation, cytokine response, and PI3K-AKT, RAS and Wnt signaling pathways. We additionally collected targeted DNA sequencing smMIPs data on a subset of ASD risk genes from 217 of the 240 ASD and TD toddlers. This DNA sequencing found about the same percentage of SFARI Level 1 and 2 ASD risk gene mutations in TD (12 of 105) as in ASD (13 of 112) toddlers, and classification based only on the presence of mutation in these risk genes performed at a chance level of 49%. By contrast, the leukocyte ensemble gene expression classifier correctly diagnostically classified 88% of TD and ASD toddlers with ASD risk gene mutations. Our ensemble ASD gene expression classifier is diagnostically predictive and replicable across different toddler ages, races, and ethnicities; out-performs a risk gene mutation classifier; and has potential for clinical translation.

The Impact of Microglia on Neurodevelopment and Brain Function in Autism

“…The PI3K/AKT signaling pathway is mainly involved in neural activities such as synaptic plasticity, neuronal development, memory consolidation, and protein synthesis [56]. The overexpression of the PI3K/AKT signaling pathway increases cell death, neuroinflammation, and oxidative stress leading to neurological diseases [57]. Research has shown that chrysophanol (CPH) can improve autismlike symptoms by inhibiting the PI3K/AKT/mTOR pathway [58].…”

Validation of plasma protein glycation and oxidation biomarkers for the diagnosis of autism

“…A diagnostic aid combining behavioural features from caregiver and healthcare provider questionnaires and home videos recently received regulatory approval by USA Food and Drug Administration (FDA) with sensitivity 98% and specificity 79% but had a high no response rate, 68% [ 8 ]. Other studies using magnetic resonance imaging (MRI) [ 9 ], visual attention/eye movement or eye tracking assessments [ 10 , 11 ], genetic mutation assessments [ 12 ] and post-natal blood tests for ASD based on transcriptomic analysis of peripheral blood mononuclear cells and proteomics and metabolomics analysis of plasma have been reported but require validation [ 13 – 16 ].…”

Exploring the correlation between genetic transcription and multi-temporal developmental autism spectrum disorder using resting-state functional magnetic resonance imaging

“…Genetic factors play a dominant role in the etiology of autism. Despite this, a limited number of articles have specifically explained changes in genetic transcription in stratified studies of ASD age ( Rahbar et al, 2015 ; Bao et al, 2023 ). The neuropathological mechanism of autism is complex, involving abnormal synaptic function, abnormal neuronal activity patterns, abnormal genes, an abnormal immune system, etc.…”