Neuropsychiatric diseases are highly heterogeneous and complex disorders, resulting from the interplay between environmental factors and multiple risk factors. In most cases, many genes contribute to the disease pathophysiology due to functional variants undermining key brain-related molecular pathways and circuits. Large scale genomic approaches are showing their potential to identify the key genetic determinants of neuropsychiatric disorders and highlight putative functional mechanisms underlying disease susceptibility. By combining genomic and proteomic approaches in diseased tissues, it is possible to search for biomarker fingerprints that may help disentangling the biological complexity of brain diseases and identifying patient subgroups that are homogeneous in terms of prognosis and drug response. Visual representation of the brain

Research directions

  • Genetic biomarkers and novel targets
    one of our main interests is the understanding of the contribution of common and rare variants to the risk of neuropsychiatric disorders as well as to intermediate phenotypes. Large scale collaborative efforts such as the Psychiatry Genomics Consortium (PGC) are helping to unravel the complexity of disorders such as schizophrenia, with more than hundred loci contributing to disease susceptibility. Thanks to consortium membership, and in collaboration with PCG members, we are investigating the association between risk variants and molecular or clinical phenotypes. In collaboration with the Psychiatry Consortium, Medicine Discovery Catapult (https://psychiatryconsortium.org/news/medicine-discovery-catapults-psychiatry-consortium-announces-new-international-collaboration-to-tackle-depression/) we are investigating one of the major genetic risk factors for depression, NEGR1, as a novel treatment target in major depressive disorder. We are also investigating the genetic basis of autism, thanks to our participation to the Italian Network for Autism (https://www.fondazioneitan.org/en/) and funds from the Simons Foundation Autism Research Initiative for a project on integrative analysis of genomic and metagenomic data (https://www.sfari.org/people/enrico-domenici/).

  • Functional genomics
    we are investigating the genetic control of gene expression in the brain as a way to elucidate the genetic basis of CNS disorders at molecular level. By intersecting transcriptomics and data derived from large scale genetic association studies, it is possible to identify causal candidates among the regulatory variants that modulate gene expression (eQTLs). We are collaborating with the CommonMind Consortium (https://www.nimhgenetics.org/resources/commonmind), a public-private effort aimed at generating and analyzing large-scale genomic data from human subjects with neuropsychiatric disorders.

  • Linking Peripheral and Central Biomarkers
    given the evidence of cross-talk between the brain and peripheral systems, we are engaged in the search for non-invasive biomarkers that may help reducing the phenotypic complexity of neuropsychiatric disorders such as depression, schizophrenia and autism, and help stratifying patients into more biologically homogeneous subtypes. In this context, proteomic and genomic tools are expanding by orders of magnitude the number of testable hypotheses and allowing for the identification of molecular signatures rather than single markers. In order to establish correlations between peripheral and central markers, as well as between preclinical and clinical biomarkers, we are pursuing research efforts both in disease collections and in translational models of disease.

Group members

  • Enrico Domenici, PI
  • Samuele Cancellieri, postdoctoral fellow
  • Samuel Perini, postdoctoral fellow
  • Beatrice Dalpedri, PhD student (collaboration with COSBI)
  • Matteo Pozzi, PhD student (collaboration with FBK)
  • Vittorio Bontempi, student (MSc in Molecular and Cellular Biotechnologies)

Motivated PhD candidates, with interest in the application of large-scale genomic and computational approaches to understand brain function in health and disease, are encouraged to contact the PI.


  • Fondazione Italian Autism Network, Verona, Italy
  • Simons Foundation Autism Research Initiative (SFARI), Simons Foundation
  • Fondazione The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI)
  • Psychiatry Consortium, Medicine Discovery Catapult UK
  • Giuseppe Jurman, FBK, Data Science for Health (DSH) Research Unit, Trento
  • Lucia Carboni, Department of Pharmacy and Biotechnology, University of Bologna, Italy
  • Massimo Gennarelli, Department of Molecular and Translational Medicine, University of Brescia, Italy
  • Alessandro Bertolino, Giulio Pergola, Psychiatric Neuroscience Group, University of Bari, Italy
  • Dheeraj Malhotra, Neuroscience Discovery, Roche, Basel, Switzerland
  • Pat Sullivan, Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, USA and Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Sweden, and the Psychiatry Genomics Consortium
  • Panos Roussos, Division of Psychiatric Genomics, Mount Sinai, NY, USA and the CommonMind Consortium
  • Mette Peters and Solly Sieberts, Sage Bionetworks, Seattle, USA
  • Carla Barbosa Nonino, Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto


Bando: PRIN 2022 (D.D. 104/22)
Translational genomics of a major schizophrenia risk factor: from cellular to clinical phenotype
Enrico Domenici, Coordinatore
Codice Protocollo: 2022Z84LT5     CUP: E53D23005060006

Selected publications

Trubetskoy V et al. (Domenici E. among PI of the Schizophrenia Working Group of the Psychiatric Genomics Consortium). Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022 Apr 8

Carboni L, Delafont B, Ivanchenko E, Ratti E, Learned SM, Alexander R, Domenici E.. Folate metabolism biomarkers from two randomised placebo-controlled clinical studies with paroxetine and venlafaxine. World J Biol Psychiatry. 2021 22:315-321.

Carboni L, Pischedda F, Piccoli G, Lauria M, Musazzi L, Popoli M, Mathé AA, Domenici E.. Depression-Associated Gene Negr1-Fgfr2 Pathway Is Altered by Antidepressant Treatment. Cells. 2020 9:1818

Filosi M, Kam-Thong T, Essioux L, Muglia P, Trabetti E, Spooren W, Müller-Myshok B; Italian Autism Network, Domenici E.. Transcriptome signatures from discordant sibling pairs reveal changes in peripheral blood immune cell composition in Autism Spectrum Disorder. Transl Psychiatry. 2020 10:106.

Marchetti L, Lauria M, Caberlotto L, Musazzi L, Popoli M, Mathé AA, Domenici E., Carboni L. Gene expression signature of antidepressant treatment response/non-response in Flinders Sensitive Line rats subjected to maternal separation. Eur Neuropsychopharmacol. 2020;31:69-85.

Misselbeck K, Parolo S*, Lorenzini F, Savoca V, Leonardelli L, Bora P, Morine MJ, Mione MC, Domenici E.*, Priami C*. A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome. Nat Commun. 2019;10:5215.

Hoffman GE, Bendl J, Voloudakis G, Montgomery KS, Sloofman L, Wang YC, Shah HR, Hauberg ME, Johnson JS, Girdhar K, Song L, Fullard JF, Kramer R, Hahn CG, Gur R, Marenco S, Lipska BK, Lewis DA, Haroutunian V, Hemby S, Sullivan P, Akbarian S, Chess A, Buxbaum JD, Crawford GE, Domenici E., Devlin B, Sieberts SK, Peters MA, Roussos P. CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder. Sci Data. 2019;6:180.

Carboni L, McCarthy DJ, Delafont B, Filosi M, Ivanchenko E, Ratti E, Learned SM, Alexander R, Domenici E.. Biomarkers for response in major depression: comparing paroxetine and venlafaxine from two randomised placebo-controlled clinical studies. Transl Psychiatry. 2019;9(1):182.

Huckins LM, Dobbyn A, Ruderfer DM, Hoffman G, Wang W, Pardiñas AF, Rajagopal VM, Als TD, T Nguyen H, Girdhar K, Boocock J, Roussos P, Fromer M, Kramer R, Domenici E., Gamazon ER, Purcell S; CommonMind Consortium; Schizophrenia Working Group of the Psychiatric Genomics Consortium; iPSYCH-GEMS Schizophrenia Working Group, Demontis D, Børglum AD, Walters JTR, O'Donovan MC, Sullivan P, Owen MJ, Devlin B, Sieberts SK, Cox NJ, Im HK, Sklar P, Stahl EA. Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nat Genet. 2019;51:659-674.

Muglia P, Filosi M, Da Ros L, Kam-Thong T, Nardocci F, Trabetti E, Ratti E, Rizzini P, Zuddas A, Bernardina BD, Italian Autism Network, Domenici E.. The Italian autism network (ITAN): a resource for molecular genetics and biomarker investigations. BMC Psychiatry. 2018;18(1):369.

Dobbyn A, Huckins LM, Boocock J, Sloofman LG, Glicksberg BS, Giambartolomei C, Hoffman GE, Perumal TM, Girdhar K, Jiang Y, Raj T, Ruderfer DM, Kramer RS, Pinto D; CommonMind Consortium, Akbarian S, Roussos P, Domenici E., Devlin B, Sklar P, Stahl EA, Sieberts SK. Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS. Am J Hum Genet. 2018;102:1169-1184.

Wray NR et al (Domenici E. among PI of the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium). Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018 May;50(5):668-681

Domenici E.. Schizophrenia genetics comes to translation. NPJ Schizophr. 2017; 3:10.

Fromer M, Roussos P, Sieberts SK, Johnson JS, Kavanagh DH, Perumal TM, Ruderfer DM, Oh EC, Topol A, Shah HR, Klei LL, Kramer R, Pinto D, Gümüş ZH, Cicek AE, Dang KK, Browne A, Lu C, Xie L, Readhead B, Stahl EA, Xiao J, Parvizi M, Hamamsy T, Fullard JF, Wang YC, Mahajan MC, Derry JM, Dudley JT, Hemby SE, Logsdon BA, Talbot K, Raj T, Bennett DA, De Jager PL, Zhu J, Zhang B, Sullivan PF, Chess A, Purcell SM, Shinobu LA, Mangravite LM, Toyoshiba H, Gur RE, Hahn CG, Lewis DA, Haroutunian V, Peters MA, Lipska BK, Buxbaum JD, Schadt EE, Hirai K, Roeder K, Brennand KJ, Katsanis N, Domenici E., Devlin B, Sklar P. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci. 2016; 19:1442-1453.

Schubert CR, O'Donnell P, Quan J, Wendland JR, Xi HS, Winslow AR, Domenici E., et al. BrainSeq: Neurogenomics to Drive Novel Target Discovery for Neuropsychiatric Disorders. Neuron 2015: 88:1078-83

Carboni L, Domenici E.. Proteome effects of antipsychotic drugs: Learning from preclinical models. Proteomics Clin Appl. 2015 Nov 9.

Schizophrenia Working Group of the Psychiatric Genomics (Domenici E. among PIs). Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014; 511:421-7

Malki K, Keers R, Tosto MG, Lourdusamy A, Carboni L, Domenici E., Uher R, McGuffin P, Schalkwyk LC. The endogenous and reactive depression subtypes revisited: integrative animal and human studies implicate multiple distinct molecular mechanisms underlying major depressive disorder. BMC Med. 2014;12:73

Tansey KE, Guipponi M, Perroud N, Bondolfi G, Domenici E. et al. Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis. PLoS Med. 2012; 9:e1001326.

Kas MJ, Krishnan V, Gould TD, Collier DA, Olivier B, Lesch KP, Domenici E., Fuchs E, Gross C, Castrén E. Advances in multidisciplinary and cross-species approaches to examine the neurobiology of psychiatric disorders. Eur Neuropsychopharmacol. 2011; 21:532-44.

Domenici E., Willé D, Tozzi F, Prokopenko I, Miller S, McKeown A, Brittain C, Rujescu D, Giegling I, Turck CW, Holsboer F, Bullmore ET, Middleton L, Merlo-Pich E, Alexander RC, Muglia P. Plasma protein biomarkers for depression and schizophrenia by multi analyte profiling of case-control collections. PLoS One 2010; 5:e9166.

Muglia P, Tozzi F, Galwey NW, Francks C, Upmanyu R, Kong XQ, Antoniades A, Domenici E. et al. Genome-wide association study of recurrent major depressive disorder in two European case-control cohorts. Mol Psychiatry 2010; 15:589-601.