Genome, Environment, Microbiome and Metabolome in Autism (GEMMA) Study Design: Biomarkers Identification for Precision Treatment and Primary Prevention of Autism Spectrum Disorders by an Integrated Multi-Omics Systems Biology Approach
Troisi, Jacopo; Autio, Reija; Beopoulos, Thanos; Bravaccio, Carmela; Carraturo, Federica; Corrivetti, Giulio; Cunningham, Stephen; Devane, Samantha; Fallin, Daniele; Fetissov, Serguei; Gea, Manuel; Giorgi, Antonio; Iris, François; Joshi, Lokesh; Kadzielski, Sarah; Kraneveld, Aletta; Kumar, Himanshu; Ladd-Acosta, Christine; Leader, Geraldine; Mannion, Arlene; Maximin, Elise; Mezzelani, Alessandra; Milanesi, Luciano; Naudon, Laurent; Marzal, Lucia N Peralta; Pardo, Paula Perez; Prince, Naika Z; Rabot, Sylvie; Roeselers, Guus; Roos, Christophe; Roussin, Lea; Scala, Giovanni; Tuccinardi, Francesco Paolo; Fasano, Alessio
(2020) Brain Sciences, volume 10, issue 10
(Article)
Abstract
Autism Spectrum Disorder (ASD) affects approximately 1 child in 54, with a 35-fold increase since 1960. Selected studies suggest that part of the recent increase in prevalence is likely attributable to an improved awareness and recognition, and changes in clinical practice or service availability. However, this is not sufficient to
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explain this epidemiological phenomenon. Research points to a possible link between ASD and intestinal microbiota because many children with ASD display gastro-intestinal problems. Current large-scale datasets of ASD are limited in their ability to provide mechanistic insight into ASD because they are predominantly cross-sectional studies that do not allow evaluation of perspective associations between early life microbiota composition/function and later ASD diagnoses. Here we describe GEMMA (Genome, Environment, Microbiome and Metabolome in Autism), a prospective study supported by the European Commission, that follows at-risk infants from birth to identify potential biomarker predictors of ASD development followed by validation on large multi-omics datasets. The project includes clinical (observational and interventional trials) and pre-clinical studies in humanized murine models (fecal transfer from ASD probands) and in vitro colon models. This will support the progress of a microbiome-wide association study (of human participants) to identify prognostic microbiome signatures and metabolic pathways underlying mechanisms for ASD progression and severity and potential treatment response.
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Keywords: microbiome, metabolomics, autism, study design, biomarker discovery, precise medicine
ISSN: 2076-3425
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
(Peer reviewed)