GEMMA, which stands for Genome, Environment, Microbiome and Metabolome in Autism, is a multicentre European Commission Project for exploring interactions between gut microbiome, metabolome, epigenome and immune function in order to discover new biomarkers useful for early diagnosis of autism and as potential targets for preventive personalized therapies.
The European Commission has selected and financed GEMMA project as part of its Horizon 2020, the biggest EU Research and Innovation programme. The grant consists of 14,2M€ in 5-years project.
GEMMA is 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 is the name for a range of similar conditions, including Asperger syndrome, that affect a person's social interaction, communication, interests and behaviour.
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.
GEMMA 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.