Pre-treatment clinical and gene expression patterns predict developmental change in 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:10.1038/s41380-021-01239-2

Cited by 8 publications

(14 citation statements)

References 85 publications

(99 reference statements)

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“…To date, research about RTT in ESDM remains sparse and most studies focusing on homogeneous and individualized therapy settings comprised limited sample size. Younger age at start has emerged as an important moderator of optimal outcome, probably due to higher brain plasticity ( 26 , 27 ). Age left aside, there are no behavioral characteristics child that are recommended by any international guidelines as a reliable individual predictor of RTT in ESDM, despite many attempts to identify some ( 14 , 28 ).…”

Section: Introductionmentioning

confidence: 99%

“…To do so, we explored the developmental trajectories of 55 preschoolers with ASD who completed 2 years of individualized and intensive (20 h per week) ESDM intervention available in Geneva, Switzerland. We used a longitudinal single group design without a control population, similar to previous studies in the field ( 25 , 26 , 29 ). Indeed, because of ethical as well as logistic considerations, a random referencing to either the ESDM intervention program or any other community treatment was not achievable.…”

Section: Introductionmentioning

confidence: 99%

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Distinct Patterns of Cognitive Outcome in Young Children With Autism Spectrum Disorder Receiving the Early Start Denver Model

et al. 2022

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Evidence-based, early intervention significantly improves developmental outcome in young children with autism. Nonetheless, there is high interindividual heterogeneity in developmental trajectories during the therapy. It is established that starting intervention as early as possible results in better developmental outcomes. But except for younger age at start, there is no clear consensus about behavioral characteristics that could provide a reliable individual prediction of a child's developmental outcome after receiving an early intervention. In this study, we analyze developmental trajectories of preschoolers with autism who received 2 years of intervention using the Early Start Denver Model (ESDM) approach in Geneva, Switzerland in an individual setting (n = 55, aged 28.7 ± 5.1 months with a range of 15–42). Our aim was to identify early predictors of response to intervention. We applied a cluster analysis to distinguish between 3 groups based on their cognitive level at intake, and rates of cognitive change over the course of intervention. The first group of children only had a mild cognitive delay at intake and nearly no cognitive delay by the end of intervention (Higher Cognitive at baseline: HC). The children in the two other groups all presented with severe cognitive delay at baseline. However, they had two very different patterns of response to intervention. The majority significantly improved developmental scores over the course of intervention (Optimal Responders: OptR) whereas a minority of children showed only modest improvement (Minimal Responders: MinR). Further analyses showed that children who ended up having an optimal 2-year intervention outcome (OptR) were characterized by higher adaptive functioning at baseline combined with rapid developmental improvement during the first 6 months of intervention. Inversely, less significant progress by the sixth month of intervention was associated with a less optimal response to treatment (MinR).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distinct Patterns of Cognitive Outcome in Young Children With Autism Spectrum Disorder Receiving the Early Start Denver Model

et al. 2022

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“…Leukocyte expression also relates to hypoactivation response to affective speech in ASD toddlers with poor language outcome [ 46 ]. Finally, multivariate leukocyte expression signatures can predict trajectories of response to early intervention treatment [ 83 ], which underscores the relevance of leukocytes to ASD and clinically important phenomena that can be individualized to specific patients. Thus, extensive literature, meta-analyses, and the predictive diagnostic discoveries in the present study, all point to the importance of leukocyte cell biology as clinically informative in ASD and show that ASD-relevant dysregulated gene expression is not restricted to the brain but is also present in other tissues and organs.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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“…To date, research about RTT in ESDM remains sparse and most studies focusing on homogeneous and individualized therapy settings comprised limited sample size. Younger age at start has emerged as an important moderator of optimal outcome, probably due to higher brain plasticity (Lombardo et al, 2021; Webb et al, 2014). Age left aside, there are no behavioral child that are recommended by any international guidelines as a reliable individual predictor of RTT in ESDM, despite many attempts to identify some (Fuentes et al, 2021; Lord et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…To do so we explored the developmental trajectories of 55 preschoolers with ASD who completed two years of individualized and intensive (20 hours per week) ESDM intervention available in Geneva, Switzerland. We used a longitudinal single group design without a control population, similar to previous studies in the field (Contaldo et al, 2020; Lombardo et al, 2021; Vivanti et al, 2013). Indeed, because of ethical as well as logistic considerations, a random referencing to either the ESDM intervention program or any other community treatment was not achievable.…”

Section: Introductionmentioning

confidence: 99%

Distinct patterns of cognitive outcome in young children with autism spectrum disorder receiving the Early Start Denver Model

Godel

Robain

Kojovic

et al. 2021

Preprint

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Evidence-based early intervention approaches have been shown to significantly improve many areas of development in young children with autism. Despite having an overall positive impact for most children, there is high inter-individual heterogeneity of response to treatment, and it is currently not possible to predict which child will benefit from which specific intervention. In this study, we analyze developmental trajectories of young children with autism who received two-years of Early Start Denver Model intervention in Geneva, Switzerland (n=47). Using cluster analyses, we distinguish between 3 subgroups based on cognitive level at baseline and rates of change over time. The first subgroup of children had cognitive scores at baseline only slightly below what would be expected for their age and were found to have nearly no cognitive delay by the end of treatment (High at Baseline: HB). The children in the two other subgroups all presented with severe cognitive delay at baseline, with the second group′s cognitive scores improving significantly in the first year of intervention, along with increased communication and daily living skills (High Responders: HR). The third subgroup showed little to no cognitive level change over the course of treatment (Minimal Responders: MR). Furthermore, the rates of change in cognition and adaptative behavior in the HR subgroup were already significantly higher compared to the MR subgroup within the first 6 months of intervention. A rapid and early response to intervention might thus represent a predictor of optimal outcome. Inversely, slower progress by the sixth month of intervention may predict that the child will have a slower response to the treatment overall and may need alternative supports to reach their learning objectives quickly.

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Pre-treatment clinical and gene expression patterns predict developmental change in early intervention in autism

Cited by 8 publications

References 85 publications

Distinct Patterns of Cognitive Outcome in Young Children With Autism Spectrum Disorder Receiving the Early Start Denver Model

Distinct Patterns of Cognitive Outcome in Young Children With Autism Spectrum Disorder Receiving the Early Start Denver Model

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

Distinct patterns of cognitive outcome in young children with autism spectrum disorder receiving the Early Start Denver Model

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