Alessandra M. Mezzelani
STAFF
Project
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 Spectrum Disorder
Name
Genome, Environment, Microbiome & Metabolome in Autism: an integrated multi-omic systems biology approach to identify biomarkers for personalized treatment and primary prevention of Autism Spectrum Disorder
Acronym
GEMMA
Location
Segrate
Start Date
2019
End Date
2025
Funder
Horizon 2020, RIA, Topic: SC1-BHC-03-2018
Partners
Fondazione Ebris, IT NUTRICIA RESEARCH BV, NL MEDINOK SpA, IT BIO MODELING SYSTEMS (BMSYSTEMS), FR EUFORMATICS OY, FI Theoreo srl, IT NATIONAL UNIVERSITY OF IRELAND GALWAY, IE ASL Salerno, IT THE GENERAL HOSPITAL CORPORATION, USA INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE (INRAE), FR INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM), FR University of Utrecht, NL University of Tampere, FI JOHNS HOPKINS UNIVERSITY, USA IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE, UK, Marco Moscatelli, Matteo Gnocchi (AREA MILANO 4)
GEMMA is the first project to integrate multi-omics analyses with robust environmental data to investigate the role of the gut microbiome in autism spectrum disorders (ASD). The project analyzes the composition and function of the microbiota to support personalized treatment strategies and early disease interception in infants at risk of ASD. By longitudinally following 500 at-risk infants from birth, GEMMA generates mechanistic insights into disease onset and progression by linking dysbiotic gut microbiota to epigenetic, immune, and gut barrier alterations. Human multi-omics data are integrated with preclinical studies using humanized murine models transplanted with patient-derived microbiota to establish causal links with clinical outcomes. GEMMA’s aims are to identify molecular and metabolic biomarkers for patient stratification and to develop microbiota-modulating preventive and therapeutic approaches. The project has also established a unique biobank of over 16,000 prospectively collected biospecimens to support future multi-omics research.
Publications
- Chiodi, Alice, Ettore Mosca, Francesca Anna Cupaioli, and Alessandra Mezzelani. 2026. “Inference of Autism Risk Genes Through Comparative Sociogenomics and Molecular Network Analysis” Genes 17, no. 4: 368. doi.org/10.3390/genes17040368
- Chiappori F, Cupaioli FA, Consiglio A, Di Nanni N, Mosca E, Licciulli VF, Mezzelani A. Analysis of Faecal Microbiota and Small ncRNAs in Autism: Detection of miRNAs and piRNAs with Possible Implications in Host-Gut Microbiota Cross-Talk. Nutrients. 2022 Mar 23;14(7):1340. doi: 10.3390/nu14071340.
- Cupaioli FA, Fallerini C, Mencarelli MA, Perticaroli V, Filippini V, Mari F, Renieri A, Mezzelani A. Autism Spectrum Disorders: Analysis of Mobile Elements at 7q11.23 Williams-Beuren Region by Comparative Genomics. Genes (Basel). 2021 Oct 12;12(10):1605. doi: 10.3390/genes12101605
- Troisi J, Autio R, Beopoulos T, Bravaccio C, Carraturo F, Corrivetti G, Cunningham S, Devane S, Fallin D, Fetissov S, Gea M, Giorgi A, Iris F, Joshi L, Kadzielski S, Kraneveld A, Kumar H, Ladd-Acosta C, Leader G, Mannion A, Maximin E, Mezzelani A, Milanesi L, Naudon L, Marzal LNP, Pardo PP, Prince NZ, Rabot S, Roeselers G, Roos C, Roussin L, Scala G, Tuccinardi FP, Fasano A. 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. Brain Sci. 2020 Oct 16;10(10):743. doi: 10.3390/brainsci10100743
- Cupaioli FA, Mosca E, Magri C, Gennarelli M, Moscatelli M, Raggi ME, Landini M, Galluccio N, Villa L, Bonfanti A, Renieri A, Fallerini C, Minelli A, Marabotti A, Milanesi L, Fasano A, Mezzelani A. Assessment of haptoglobin alleles in autism spectrum disorders. Sci Rep. 2020 May 8;10(1):7758. doi: 10.1038/s41598-020-64679-w
- Di Nanni N, Bersanelli M, Cupaioli FA, Milanesi L, Mezzelani A, Mosca E. Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders. Int J Mol Sci. 2019 Jul 9;20(13):3363. doi: 10.3390/ijms20133363.
- Mosca E, Bersanelli M, Gnocchi M, Moscatelli M, Castellani G, Milanesi L, Mezzelani A. Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules. Front Genet. 2017 Sep 25;8:129. doi: 10.3389/fgene.2017.00129.
- De Santis B, Brera C, Mezzelani A, Soricelli S, Ciceri F, Moretti G, Debegnach F, Bonaglia MC, Villa L, Molteni M, Raggi ME. Role of mycotoxins in the pathobiology of autism: A first evidence. Nutr Neurosci. 2019 Feb;22(2):132-144. doi: 10.1080/1028415X.2017.1357793.
- De Santis B, Raggi ME, Moretti G, Facchiano F, Mezzelani A, Villa L, Bonfanti A, Campioni A, Rossi S, Camposeo S, Soricelli S, Moracci G, Debegnach F, Gregori E, Ciceri F, Milanesi L, Marabotti A, Brera C. Study on the Association among Mycotoxins and other Variables in Children with Autism. Toxins (Basel). 2017 Jun 29;9(7):203. doi: 10.3390/toxins9070203.
- Mezzelani A, Raggi ME, Marabotti A, Milanesi L. Ochratoxin A as possible factor triggering autism and its male prevalence via epigenetic mechanism. Nutr Neurosci. 2016;19(1):43-6. doi: 10.1179/1476830515Z.000000000186.
- Mezzelani A, Landini M, Facchiano F, Raggi ME, Villa L, Molteni M, De Santis B, Brera C, Caroli AM, Milanesi L, Marabotti A. Environment, dysbiosis, immunity and sex-specific susceptibility: a translational hypothesis for regressive autism pathogenesis. Nutr Neurosci. 2015 May;18(4):145-61. doi: 10.1179/1476830513Y.0000000108.
