Dataset Information

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project.

ABSTRACT:

Background

Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.

Methods

All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data.

Results

Deviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002). The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features.

Conclusions

Individuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.

SUBMITTER: Looden T

PROVIDER: S-EPMC9793684 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project.

Looden Tristan T Floris Dorothea L DL Llera Alberto A Chauvin Roselyne J RJ Charman Tony T Banaschewski Tobias T Murphy Declan D Marquand Andre F AF Buitelaar Jan K JK Beckmann Christian F CF

Molecular autism 20221227 1

<h4>Background</h4>Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.<h4>Methods</h4>All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism P ...[more]

PMID: 36575450

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Project description:BackgroundThe EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study on biomarkers for autism spectrum disorder (ASD). The current paper describes the clinical characteristics of the LEAP cohort and examines age, sex and IQ differences in ASD core symptoms and common co-occurring psychiatric symptoms. A companion paper describes the overall design and experimental protocol and outlines the strategy to identify stratification biomarkers.MethodsFrom six research centres in four European countries, we recruited 437 children and adults with ASD and 300 controls between the ages of 6 and 30 years with IQs varying between 50 and 148. We conducted in-depth clinical characterisation including a wide range of observational, interview and questionnaire measures of the ASD phenotype, as well as co-occurring psychiatric symptoms.ResultsThe cohort showed heterogeneity in ASD symptom presentation, with only minimal to moderate site differences on core clinical and cognitive measures. On both parent-report interview and questionnaire measures, ASD symptom severity was lower in adults compared to children and adolescents. The precise pattern of differences varied across measures, but there was some evidence of both lower social symptoms and lower repetitive behaviour severity in adults. Males had higher ASD symptom scores than females on clinician-rated and parent interview diagnostic measures but not on parent-reported dimensional measures of ASD symptoms. In contrast, self-reported ASD symptom severity was higher in adults compared to adolescents, and in adult females compared to males. Higher scores on ASD symptom measures were moderately associated with lower IQ. Both inattentive and hyperactive/impulsive ADHD symptoms were lower in adults than in children and adolescents, and males with ASD had higher levels of inattentive and hyperactive/impulsive ADHD symptoms than females.ConclusionsThe established phenotypic heterogeneity in ASD is well captured in the LEAP cohort. Variation both in core ASD symptom severity and in commonly co-occurring psychiatric symptoms were systematically associated with sex, age and IQ. The pattern of ASD symptom differences with age and sex also varied by whether these were clinician ratings or parent- or self-reported which has important implications for establishing stratification biomarkers and for their potential use as outcome measures in clinical trials.

Project description:BackgroundThe tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD.MethodsLEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability.ResultsHere, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some 'lessons learnt'. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted).ConclusionWe expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.

Project description:Project ECHO (Extension for Community Healthcare Outcomes) was developed in 2003 as an innovative model to facilitate continuing education and professional development. ECHO emphasizes 'moving knowledge, not people.' To accomplish this, ECHO programs use virtual collaboration and case-based learning to allow practitioners, including those in rural and underserved areas, to receive specialist training. The ECHO model has expanded rapidly and is now used in 44 countries. Preliminary research on ECHO's efficacy and effectiveness has shown promising results, but evidence remains limited and appropriate research outcomes have not been clearly defined. To improve the evidence basis for ECHO, this study of 5 ECHO programs (cancer prevention/survivorship, integrated pain management, hepatitis C, HIV, and LGBTQ+ health care elucidated actionable insights about the ECHO programs and directions in which future evaluations and research might progress. This was a qualitative study following COREQ standards. A trained interviewer conducted 10 interviews and 5 focus groups with 25 unique, purposively sampled ECHO attendees (2 interviews and 1 focus group for each of the 5 programs). Data were transcribed verbatim and analyzed using the general inductive approach, then reviewed for reliability. We identified four major categories (reasons to join ECHO, value of participating in ECHO, ways to improve ECHO, and barriers to participation) composed of 23 primary codes. We suggest that thematic saturation was achieved, and a coherent narrative about ECHO emerged for discussion. Participants frequently indicated they received valuable learning experiences and thereby changed their practice; rigorous trials of learning and patient-level outcomes are warranted. This study also found support for the idea that the ECHO model should be studied for its role in convening communities of practice and reducing provider isolation as an outcome in itself. Additional implications, including for interprofessional education and model evolution, were also identified and discussed.

Dataset Information

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project.

Background

Methods

Results

Conclusions

Publications

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project.

Similar Datasets

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