Neuroscience

14 Aprile 2021, 10.00 - 11.20

Decomposing Heterogeneity in the AUTISMS

Michael Vincent Lombardo

(Istituto Italiano di Tecnologia)

Laboratory for Autism and Neurodevelopmental Disorders (LAND)

Center for Neuroscience and Cognitive Systems (CNCS)
Istituto Italiano di Tecnologia (IIT)
Google Scholar Profile

(https://www.iit.it/people/michael-lombardo)

Venue:

14/4/2021; 10.00 am

Abstract

Autism spectrum conditions (ASC) occur in 1-2% of the population and are a major public health issue. Heterogeneity between  ASC individuals is substantial both at clinical and etiological levels, thus warranting the idea that we should begin characterizing the ASC population as multiple kinds of ‘autisms’. Without an advanced understanding of how heterogeneity manifests in ASC, it is likely that we will not make pronounced progress towards translational research goals that can have real impact on people's lives. In this talk, I will show examples from my research program focused on decomposing heterogeneity in ASC at multiple levels of analysis. Using multiple ‘big data’ resources that are both ‘broad’ (large sample size) and ‘deep’ (multiple levels of analysis measured within each individual), I will examine how known variables such as sex, early language development, early social preferences, and early intervention response may be important stratification variables that differentiate ASC subgroups at phenotypic, neural systems/circuits, and genomic levels of analysis. In addition to examining known stratification variables, I will show examples of data-driven discovery via application of advanced unsupervised computational techniques that can highlight novel multivariate distinctions in the data that signal important ASC subgroups. These data-driven approaches may hold promise for discovering novel ASC subgroups at biological and phenotypic levels of analysis that may be valuable for prioritization in future work developing personalized assessment, monitoring, and intervention strategies for subsets of the ASC population. 

Host

CoSAN Lab meeting
https://phd.uniroma1.it/web/pagina.aspx?i=3533&l=EN&p=48