Pre-treatment clinical behavioral and blood leukocyte gene expression patterns predict rate of change in response to early intervention in autism

Lombardo, Michael; Busuoli, Elena Maria; Schreibman, Laura; Stahmer, Aubyn C.; Pramparo, Tiziano; Landi, Isotta; Mandelli, Veronica; Bertelsen, Natasha; Barnes, Cynthia Carter; Gazestani, Vahid H.; Lopez, Linda; Bacon, Elizabeth; Courchesne, Eric; Pierce, Karen

doi:10.1101/2020.12.21.20248674

Cited by 3 publications

(3 citation statements)

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“…Finally, we found multivariate leukocyte expression signatures can predict trajectories of response to early intervention treatment 52 , which underscores the mechanistic relevance of leukocytes to ASD and clinically important phenomena that can be individualized to specific patients.…”

Section: Discussionmentioning

confidence: 59%

A Highly Accurate Ensemble Classifier for the Molecular Diagnosis of ASD at Ages 1 to 4 Years

Bao

Xiao

et al. 2021

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ImportanceASD diagnosis remains behavior-based and the median age of the first diagnosis remains unchanged at ∼52 months, which is nearly 5 years after its first trimester origin. Long delays between ASD’s prenatal onset and eventual diagnosis likely is a missed opportunity. However, accurate and clinically-translatable early-age diagnostic methods do not exist due to ASD genetic and clinical heterogeneity. There is a need for early-age diagnostic biomarkers of ASD that is robust against its heterogeneity.ObjectiveTo develop a single blood-based molecular classifier that accurately diagnoses ASD at the age of first symptoms.Design, Setting, and ParticipantsN=264 ASD, typically developing (TD), and language delayed (LD) toddlers with their clinical, diagnostic, and leukocyte RNA data collected. Datasets included Discovery (n=175 ASD, TD subjects), Longitudinal (n=33 ASD, TD subjects), and Replication (n=89 ASD, TD, LD subjects). We developed an ensemble of ASD classifiers by testing 42,840 models composed of 3,570 feature selection sets and 12 classification methods. Models were trained on the Discovery dataset with 5-fold cross validation. Results were used to construct a Bayesian model averaging-based (BMA) ensemble classifier model that was tested in Discovery and Replication datasets. Data were collected from 2007 to 2012 and analyzed from August 2019 to April 2021.Main Outcomes and MeasuresPrimary outcomes were (1) comparisons of the performance of 42,840 classifier models in correctly identifying ASD vs TD and LD in Discovery and Replication datasets; and (2) performance of the ensemble model composed of 1,076 models and weighted by Bayesian model averaging technique.ResultsOf 42,840 models trained in the Discovery dataset, 1,076 averaged AUC-ROC>0.8. These 1,076 models used 191 different feature routes and 2,764 gene features. Using weighted BMA of these features and routes, an ensemble classifier model was constructed which demonstrated excellent performance in Discovery and Replication datasets with ASD classification AUC-ROC scores of 84% to 88%. ASD classification accuracy was comparable against LD and TD subjects and in the Longitudinal dataset. ASD toddlers with ensemble scores above and below the ASD ensemble mean had similar diagnostic and psychometric scores, but those below the ASD ensemble mean had more prenatal risk events than TD toddlers. Ensemble features include genes with immune/inflammation, response to cytokines, transcriptional regulation, mitotic cell cycle, and PI3K-AKT, RAS, and Wnt signaling pathways.Conclusions and RelevanceAn ensemble ASD molecular classifier has high and replicable accuracy across the spectrum of ASD clinical characteristics and across toddlers aged 1 to 4 years, which has potential for clinical translation.Key PointsQuestionSince ASD is genetically and clinical heterogeneous, can a single blood-based molecular classifier accurately diagnose ASD at the age of first symptoms?FindingsTo address heterogeneity, we developed an ASD classifier method testing 42,840 models. An ensemble of 1,076 models using 191 different feature routes and 2,764 gene features, weighted by Bayesian model averaging, demonstrated excellent performance in Discovery and Replication datasets producing ASD classification with the area under the receiver operating characteristic curve (AUC-ROC) scores of 84% to 88%. Features include genes with immune/inflammation, response to cytokines, transcriptional regulation, mitotic cell cycle, and PI3K-AKT, RAS and Wnt signaling pathways.MeaningAn ensemble gene expression ASD classifier has high accuracy across the spectrum of ASD clinical characteristics and across toddlers aged 1 to 4 years.

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Section: Discussionmentioning

confidence: 59%

A Highly Accurate Ensemble Classifier for the Molecular Diagnosis of ASD at Ages 1 to 4 Years

Bao

Xiao

et al. 2021

Preprint

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Section: Introductionmentioning

confidence: 98%

“…Importantly, research shows that interventions delivered during the first 2 years of life lead to greater impact on developmental trajectories and symptom severity in comparison to interventions started later (4). In Lombardo et al 's study (4), children starting intervention during the first 24 months of age demonstrated predictable gains, while it was not the case for children starting intervention later. Moreover, in their recent study, Guthrie et al (5) showed that children starting a parent-mediated intervention, the Early Social Interaction (ESI) model, at 17 months of age, showed greater gains in receptive/expressive language, social communication, and daily living skills in comparison to children beginning the same intervention at 27 months of age.…”

Section: Introductionmentioning

confidence: 98%

Case report: Preemptive intervention for an infant with early signs of autism spectrum disorder during the first year of life

et al. 2023

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Autism spectrum disorder (ASD) includes neurodevelopmental conditions traditionally considered to bring life long disabilities, severely impacting individuals and their families. Very early identification and intervention during the very first phases of life have shown to significantly diminish symptom severity and disability, and improve developmental trajectories. Here we report the case of a young child showing early behavioral signs of ASD during the first months of life, including diminished eye contact, reduced social reciprocity, repetitive movements. The child received a pre-emptive parent mediated intervention based on the Infant Start, an adaptation of the Early Start Denver Model (ESDM), specifically developed for children with ASD signs during the first year of life. The child here described received intervention from 6 to 32 months of age, in combination with educational services. Diagnostic evaluations performed at several time points (8, 14, 19, and 32 months) showed progressive improvements in his developmental level and ASD symptoms. Our case study supports the possibility of identifying ASD symptoms and providing services as soon as concerns emerge even during the first year of life. Our report, in combination with recent infant identification and intervention studies, suggests the need for very early screening and preemptive intervention to promote optimal outcomes.

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Atypical genomic patterning of the cerebral cortex in autism with poor early language outcome

Lombardo

Eyler

Pramparo

et al. 2020

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Cortical regional identities develop through anterior-posterior (A-P) and dorsal-ventral (D-V) prenatal genomic patterning gradients. Here we find that A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT) is intact in typically developing and autistic toddlers with good language outcome, but is absent in autistic toddlers with poor early language outcome. Genes driving this effect are prominent in midgestational A-P and D-V gene expression gradients and prenatal cell types driving SA and CT variation (e.g., progenitor cells versus excitatory neurons). These genes are also important for vocal learning, human-specific evolution, and prenatal co-expression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be linked to atypical genomic cortical patterning starting in prenatal periods and which impacts later development of regional functional specialization and circuit formation.

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Pre-treatment clinical behavioral and blood leukocyte gene expression patterns predict rate of change in response to early intervention in autism

Cited by 3 publications

References 80 publications

A Highly Accurate Ensemble Classifier for the Molecular Diagnosis of ASD at Ages 1 to 4 Years

A Highly Accurate Ensemble Classifier for the Molecular Diagnosis of ASD at Ages 1 to 4 Years

Case report: Preemptive intervention for an infant with early signs of autism spectrum disorder during the first year of life

Atypical genomic patterning of the cerebral cortex in autism with poor early language outcome

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