CANSAS · Clustering functional connectivity alterations in Autism Spectrum Disorders
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2020-12-01 → 2024-12-30
- EU contribution
- €269,003
- Participants
- 2
- Scheme
- MSCA-IF
Lines connect the coordinator with its partners.
Results in brief
Clustering functional connectivity alterations in Autism Spectrum Disorders
Autism spectrum disorder is a complex neuropsychiatric condition that affects more than 1 in 100 children. This condition varies considerably across individuals. One of the most prevalent challenges in autism research is to decipher this variability and break it down into meaningful subtypes. Brain imaging methods such as rsfMRI mapping have revealed that people with autism show atypical functional communication (or “connectivity”) among brain regions. However, the origin of the brain imaging findings remains unclear. For example, the link between genetic variants associated with autism and fMRI disconnectivity is largely unknown. Using recent technology of fMRI mapping in rodents, here we identify distinct and convergent functional disconnectivity patterns across autism-relevant genetic models. These findings suggest that heterogeneous functional connectivity in ASD may encode etiologically-relevant information. By using these data, here we show that the patterns of functional dysconnectivity observed across our autism-relevant mouse models can be identified and decoded in a large collection of rsfMRI scans of individuals with idiopathic ASD.
Data: CORDIS, © European Union
Project objective
Autism spectrum disorders (ASD) are among the most heritable developmental disorders, associated with a large number of rare genetic alterations. A critical goal of current ASD research is to deconstruct its heterogeneity into clinically homogeneous sub-set of patients, characterized by distinct neurobiological or functional deficits, amenable to precise therapeutic targeting. Fostered by the advent of resting-state fMRI (rsfMRI), human brain mapping has revealed highly heterogeneous patterns of neural synchronization (i.e. “functional connectivity”) in ASD, with evidence of inconsistent, often contrasting, patterns of over- and under-connectivity across patient cohorts. However, the origin and significance of these highly heterogeneous findings remain unclear: does genetic heterogeneity account for the observed network divergences? And can we use functional connectivity fingerprints to cluster ASD into clinically relevant sub-types? The present project leverages translationally-relevant mouse brain rsfMRI measurements to propose a first-of-its-kind decomposition of human ASD rsfMRI datasets into homogeneous sub-types, recapitulating biologically-validated “ground truth” network features identified in the mouse. To this aim, I will use a set of etiologically-relevant rsfMRI fingerprints identified in a unique mouse datasets comprising 20 ASD-associated mutations to guide clustering of a large collection of human rsfMRI datasets. Socio-cognitive profiling will be employed to probe the clinical significance and homogeneity of the identified clusters. I will next combine advanced statistical modelling and gene ontologies to explore the biological underpinnings of each identified connectivity sub-type. These investigations will lead to a novel, etiologically-relevant deconstruction of the connectional and clinical heterogeneity of ASD that may improve patient stratification, guide the identification of dysfunctional pathways and help prediction of treatment response.
Original text from CORDIS.
Participants
- FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA · GenovaCoordinatorItaly
- CHILD MIND INSTITUTE, INC · NEW YORKUnited States
Links
Data: CORDIS, © European Union