E Di Gregorio1,2, E Riberi3, E F Belligni3, E Biamino3, M Spielmann4, U Ala5,6, A Calcia1, I Bagnasco7, D Carli1, G Gai2, M Giordano8, A Guala9, R Keller10, G Mandrile2,11, C Arduino2, A Maffè12, V G Naretto2, F Sirchia12, L Sorasio13, S Ungari12, A Zonta2, G Zacchetti2,8, F Talarico2, P Pappi2, S Cavalieri1, E Giorgio1, C Mancini1, M Ferrero1, A Brussino1, E Savin2, M Gandione14, A Pelle11,15, D F Giachino11,15, M De Marchi11,15, G Restagno16, P Provero5,6, M Cirillo Silengo3, E Grosso2, J D Buxbaum17,18,19,20,21,22, B Pasini12, S De Rubeis17,18, A Brusco1,2, G B Ferrero3. 1. University of Torino, Department of Medical Sciences, Turin, Italy. 2. Medical Genetics Unit, Città della Salute e della Scienza University Hospital, Turin, Italy. 3. Department of Public Health and Pediatrics, University of Torino, Turin, Italy. 4. Research Group Mundlos, Max Planck Institute for Molecular Genetics, Berlin, Germany. 5. Computational Biology Unit, Molecular Biotechnology Center (MBC), Turin, Italy. 6. Department of Molecular Biotechnology and Health Sciences, University of Torino, Turin, Italy. 7. Neuropsichiatria Infantile, Martini Hospital, ASL TO1, Turin, Italy. 8. Department of Health Sciences, Laboratory of Genetics, University of Eastern Piedmont and Interdisciplinary Research Center of Autoimmune Diseases, Novara, Italy. 9. SOC Pediatria, Castelli Hospital, Verbania, Italy. 10. Mental Health Department, ASL TO2, Adult Autism Center, Turin, Italy. 11. Medical Genetics, San Luigi Gonzaga University Hospital, Orbassano (TO), Italy. 12. Molecular Biology and Genetics Unit, Santa Croce e Carle Hospital, Cuneo, Italy. 13. Pediatrics, Santa Croce e Carle Hospital, Cuneo, Italy. 14. Department of Neuropsychiatry, University of Torino, Turin, Italy. 15. Department of Clinical and Biological Sciences, University of Torino, Turin, Italy. 16. Laboratory of Molecular Genetics, Città della Salute e della Scienza University Hospital, Turin, Italy. 17. Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York. 18. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York. 19. Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York. 20. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York. 21. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York. 22. Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Abstract
BACKGROUND: Array-comparative genomic hybridization (array-CGH) is a widely used technique to detect copy number variants (CNVs) associated with developmental delay/intellectual disability (DD/ID). AIMS: Identification of genomic disorders in DD/ID. MATERIALS AND METHODS: We performed a comprehensive array-CGH investigation of 1,015 consecutive cases with DD/ID and combined literature mining, genetic evidence, evolutionary constraint scores, and functional information in order to assess the pathogenicity of the CNVs. RESULTS: We identified non-benign CNVs in 29% of patients. Amongst the pathogenic variants (11%), detected with a yield consistent with the literature, we found rare genomic disorders and CNVs spanning known disease genes. We further identified and discussed 51 cases with likely pathogenic CNVs spanning novel candidate genes, including genes encoding synaptic components and/or proteins involved in corticogenesis. Additionally, we identified two deletions spanning potential Topological Associated Domain (TAD) boundaries probably affecting the regulatory landscape. DISCUSSION AND CONCLUSION: We show how phenotypic and genetic analyses of array-CGH data allow unraveling complex cases, identifying rare disease genes, and revealing unexpected position effects.
BACKGROUND: Array-comparative genomic hybridization (array-CGH) is a widely used technique to detect copy number variants (CNVs) associated with developmental delay/intellectual disability (DD/ID). AIMS: Identification of genomic disorders in DD/ID. MATERIALS AND METHODS: We performed a comprehensive array-CGH investigation of 1,015 consecutive cases with DD/ID and combined literature mining, genetic evidence, evolutionary constraint scores, and functional information in order to assess the pathogenicity of the CNVs. RESULTS: We identified non-benign CNVs in 29% of patients. Amongst the pathogenic variants (11%), detected with a yield consistent with the literature, we found rare genomic disorders and CNVs spanning known disease genes. We further identified and discussed 51 cases with likely pathogenic CNVs spanning novel candidate genes, including genes encoding synaptic components and/or proteins involved in corticogenesis. Additionally, we identified two deletions spanning potential Topological Associated Domain (TAD) boundaries probably affecting the regulatory landscape. DISCUSSION AND CONCLUSION: We show how phenotypic and genetic analyses of array-CGH data allow unraveling complex cases, identifying rare disease genes, and revealing unexpected position effects.
Authors: Mary C Whitman; Silvio Alessandro Di Gioia; Wai-Man Chan; Alon Gelber; Brandon M Pratt; Jessica L Bell; Thomas E Collins; James A Knowles; Christopher Armoskus; Michele Pato; Carlos Pato; Sherin Shaaban; Sandra Staffieri; Sarah MacKinnon; Gail D E Maconachie; James E Elder; Elias I Traboulsi; Irene Gottlob; David A Mackey; David G Hunter; Elizabeth C Engle Journal: Invest Ophthalmol Vis Sci Date: 2020-08-03 Impact factor: 4.799
Authors: Roberta Milone; Roberta Scalise; Rosa Pasquariello; Stefano Berloffa; Ivana Ricca; Roberta Battini Journal: Genes (Basel) Date: 2021-03-31 Impact factor: 4.096