GEMMA · Genome, Environment, Microbiome & Metabolome in Autism: an integrated multi-omic systems biology approach to identify biomarkers for personalized treatment and primary prevention of Autism Spectr

GEMMA will be the first project to combine a multi-omic approach with robust environmental data to exploit the analysis of the composition and function of the microbiome for personalized treatment and, ultimately, disease interception in infants at risk of Autistic Spectrum Disorders (ASD) . The project will provide solid mechanistic evidence of the disease onset and progression in relation to dynamic changes in abnormal gut microbiota causing epigenetic modifications controlling gut barrier and immune functions, based on the in-depth evaluation of 600 infants at risk observed from birth and followed over time. These data will be integrated with pre-clinical studies to mechanistically link human microbiota composition/function with clinical outcome through humanized murine models transplanted with stools obtained from the ASD proband patient of recruited families.The project will support novel personalized prediction (personalized treatment) and disease interception (prevention) approaches that attempt to modulate gut microbiota to re-establish/maintain immune homeostasis. The biomarkers identified in this project will contribute to a better understanding of the pathogenesis of ASD in at-risk children and the possibility to manipulate the microbiota through pre/pro/symbiotic administration for prevention and treatment, a complete paradigm shift in ASD pathogenesis and early intervention. The identification of specific ASD metabolic phenotypes will further aid to define biomarkers that can be used as diagnostic tools and patient stratification models for other conditions in which the interplay between genome, microbiome and metabolic profile has been suspected or proved.Finally, the project will collect biospecimens from a cohort of 600 infants as risk of ASD observed from birth, generating a unique biobank of 16,000+ blood, stool, urine and saliva samples prospectively collected that can be exploited in future multiomic studies.