Methodological developments have equipped scientists with unprecedented opportunities to characterize brain structure and functional organization and relate it to behaviour. Yet to date, no clinically relevant tools, grounded in this neurobiology, have been developed that inform clinical outcomes in psychiatric disorders. Specifically, in autism – one of the most common neurodevelopmental conditions – there is still little knowledge about the neurobiological underpinnings of different clinical outcomes with regard to core symptoms and adaptive daily living skills. While some individuals worsen, others do better over time. Like in many realms of medicine where biomarkers have revolutionized treatment, there is also an urgent need to develop such neurobiologically-grounded predictors for clinical outcomes in autism. To date, the majority of studies have analysed small, cross-sectional samples across single neuroimaging modalities with case-control comparisons to find mean group effects. However, this standard approach ignores the large sample variation in autism. The overarching objective of my MSCA Fellowship is to establish a multimodal, longitudinal characterization of the individual neurobiological signatures that are predictive of clinical outcomes in autism. I will integrate both structural and functional neuroimaging modalities for a fine-grained characterization of the neural phenotypes in autism. Using normative modelling, I will characterize at the level of the individual (rather than with group averages) how each individual with autism is different from the neurotypical pattern of such a multimodal brain characterization and how it relates to behaviour, genetic risk and clinical outcome. This novel approach has the potential to transform clinical management in autism, leading to the development of neuroscientifically-informed, targeted interventions. I will also provide the research community with novel tools that pave the way for precision medicine.
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