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

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 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.

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

“…For example, one could imagine two metabolites that have the same concentrations in TD and ASD, but whose correlation changes with age or other conditions (e.g, diet; example [ 48 ]). Much of the literature on biomarkers of ASD and/or IDD has focused on the search for individual molecules, or statistical combinations of molecules, which are predictive of ASD-related morbidity or diagnosis [ 16 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 ]. However, few metabolomic studies have moved beyond individual, isolated biomarkers, focusing instead on metabolic pathway analysis, in which whole metabolic pathways are analyzed for significant changes.…”

Gut Reactions: How Far Are We from Understanding and Manipulating the Microbiota Complexity and the Interaction with Its Host? Lessons from Autism Spectrum Disorder Studies

“…Again, the European Commission, showing great attention to these aspects, promotes the creation of an international consortium, whose aim is to longitudinally investigate the differences in microbiome evolution in children who develop ASD. To do so, the GEMMA consortium [91] will follow 600 at-risk babies who were born from parents who already raise an ASD-affected son. The hope is that the analysis of the evolution of the gut microbiome, corrected to all the possible confounders (environmental effects, drug taken, genetic effects, and so on and so forth), will allow a specific factor(s) to be described (or some) that will start a cascade of events, which eventually culminate in the disease onset.…”

Autism Spectrum Disorders: Analysis of Mobile Elements at 7q11.23 Williams–Beuren Region by Comparative Genomics

“…ASD has a complex and uncertain etiology, mainly due to gene-environment interaction. As for the environment, endocrine disruptors and intestinal microbes are getting a great attention from the scientific community [5][6][7]. Although genetics plays a key role in ASD etiology and hundreds of causative genetic and risk factors have been described, only 25-30% of patients carry genetic variants [8].…”

“…Between these two regions, we focused on results including a gene with the highest score and identity. Interestingly, dog Cfa6 7. aligns with human neurexin (NRXN3) (Chr14:79,081,617-79,081,678) with 11% of coverage and 78% of identity.…”