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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

Periodic Reporting for period 2 - 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)

Reporting period: 2020-01-01 to 2021-06-30

GEMMA has received funding from the EU Horizon 2020 programme under Grant Agreement No 825033. GEMMA aims to employ an integrated multi-omic systems biology approach to identify biomarkers for personalized treatment and primary prevention of Autism Spectrum Disorders (ASD). The project plan will consist on recruiting 600 infants at risk of autism and analyze, at multi-omics level, their biological samples over a 36 month period along the project’s 5-years-period, followed by an interventional arm to manipulate the gut microbiome in order to mitigate infiammation both at the gastrointestinal level and in the brain of children that will develop ASD during the study. It has been widely demonstrated that ASD is not a single disorder, but a spectrum of related disorders with a shared core of symptoms defined by deficits in communication, social reciprocity and repetitive, stereotypic behaviors. ASD represent a significant public health issue since it dramatically increased in the last decades reaching the prevalence of 1 in 59 children around the world with a strong sex bias (4:1 male:female ratio). Moreover, it was found that in families with a children with ASD, the chances that a siblings will develop autism are around one in five, thus considering the presence of inherited risk factors. Many individuals with ASD suffer from associated co-morbidities (i.e. metabolic conditions, and gastrointestinal disorders), and the neuroanatomical and biochemical characteristics associated with autism pathogenesis involve mechanisms that are direct consequences of the effects of systemic inflammatory events. The scope of the project is to use high quality microbiome, metabolome, and other -omics data to link microbiome composition and function with specific disease for personalized prediction, prevention, and treatment of disease: the prospective study to identify potential biomarkers, able to predict ASD development followed by validation on large multi-omic datasets will be the main goal of GEMMA. 3 infants recruitment centers will allow a global sampling based on their geographical coverage (Europe and US) and their broad network, which will facilitate the recruitment of 600 newborns in families already with a child suffering from ASD. GEMMA workflow was based on two non-mutually exclusive hypotheses: the first, affirming that the gut bacterial dysbiosis leads to epigenetic modifications, changes in metabolite profiles, increased gut permeability, increased macromolecules trafficking and, ultimately, to altered immune responses to promote disease in a subset of individuals at-risk of ASD; the second, asserting that the genome/metagenome interplay is responsible for the switch from immune tolerance to immune response to environmental stimuli, including dietary and microbial factors leading to neuroinflammation responsible of behavioral changes that characterize ASD and gut inflammation causing its GI co-morbidities.
Sars-Cov2 pandemic highly hampered recruitment of newborns at-risk of ASD and their family members and, consequently, the number of individuals enrolled and specimens collected is less than expected. Once the activity has been resumed the recruitment process is going fast, as expected at the beginning of GEMMA. Also the omic samples analyses were impaired by the strong limitations imposed by the lockdown in most of partners’ facilities. Nevertheless, GEMMA is in progress taking advantages from the data produced by CD-GEMM project (a project operated at Boston from Prof. Fasano on celiac disease) that has a study design like GEMMA. Indeed, GEMMA capitalized on the CD-GEMM setup and development of bioanalytical methods and bioinformatic tools that can be applied to GEMMA once samples/data become available: set up of an analysis environment for large datasets containing sensitive data; optimization of serum metabolomic analysis; improvement of omnomics NGSl pipeline and MetaboPredict tool; improvement of network-based and pathway-based methods for the identification of molecular players associated with ASD, using multi-omics data available in other projects; development of a complete and integrated catalogue for human microbiota. As for proteomics, two candidate oxytocin-like bacterial proteins have been identified in Lactobacillus salivarius. Oxytocin-like effects will be analyzed, both direct (on oxytocin receptor) or indirect (production of oxytocin-cross reactive autoantibodies) and, if confirmed, the presence of the strain and the proteins will be analyzed in the GEMMA samples since oxytocin signaling is relevant to social behavior. GEMMA is also implementing a biorepository and an open data repository. For the biorepository, EBRIS designed a "Collection Protocol" to share with the recruitment centers. The GEMMA Open Data Repository prototype was designed and is still in progress. Partners involved in Pre-Clinical Trials are working for defining the microbiota strain composition, by 16rRNA-seq, (in progress) and the metabolic activity (completed) of all the stool collected till now from children with ASD, with or without GI symptoms, and their unaffected siblings. They are also testing the effects of ingredients (pre-, pro- and symbiotics) on all the stool samples to study the impact of these ingredients on the metabolic changes and microbiota composition during in vitro fermentation experiments performed in BioLector. Then again, fecal microbiota transplantation from all the children with ASD and their siblings into two different strains of germ-free recipient mice was performed and the effect of these microbiota evaluated by behavioral tests. We have formulated and finalized non-mutually exclusive mechanistic pathway hypotheses that were presented in a manuscript that has been submitted for publication and currently under review. Two additional manuscripts are in the process to be submitted as well. Communication and dissemination activities were carried on maximizing the connection with the stakeholders. During Sars-Cov2 we focused on social media to offer a sort of “service” for supporting children with ASD, families and educators with educational/entertainment activities, surveys and webinars. A cartoon character, a girl named GEMMA, was also created to communicate the project and to launch a drawing contest. The project website was updated with news and events. A total of 10 scientific articles were published on peer reviewed international journals in open access mode.
GEMMA consortium has been creating a tight network to ease multi-omics data exchange between the leading research groups in Europe and the US. The main purpose will be the generation of a continuously updated multi-omics open data portal for autism, integrated with existing omics databases. The availability of a biobank, composed by specimens collected from a cohort of 600 infants as risk of ASD, observed from birth, may leverage future multi-omics studies, not only for ASD, but for the majority of multi-factorial disorders. The expected results will be promptly shared during the project, with an increasingly strengthened open data management, complemented with dynamic data analysis, for the identification of reliable markers to efficiently diagnosing autism. The opportunity to diagnose ASD, predicting the onset of clinical manifestations, may allow the primary prevention, by intervening with tailored probiotic therapies.
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