Correlating Neuroimaging and CNVs Data: 7 Years of Cytogenomic Microarray Analysis on Patients Affected by Neurodevelopmental Disorders

Abstract

The aim of this study was to evaluate the relationship between neurodevelopmental disorders, brain anomalies, and copy number variations (CNVs) and to estimate the diagnostic potential of cytogenomical microarray analysis (CMA) in individuals neuroradiologically characterized with intellectual developmental disorders (IDDs) isolated or associated with autism spectrum disorders (ASDs) and epilepsy (EPI), all of which were identified as a “synaptopathies.” We selected patients who received CMA and brain magnetic resonance imaging (MRI) over a 7-year period. We divided them into four subgroups: IDD, IDD + ASD, IDD + EPI, and IDD + ASD + EPI. The diagnostic threshold of CMA was 16%. The lowest detection rate for both CMA and brain anomalies was found in IDD + ASD, while MRI was significantly higher in IDD and IDD + EPI subgroups. CMA detection rate was significantly higher in patients with brain anomalies, so CMA may be even more appropriate in patients with pathological MRI, increasing the diagnostic value of the test. Conversely, positive CMA in IDD patients should require an MRI assessment, which is more often associated with brain anomalies. Posterior fossa anomalies, both isolated and associated with other brain anomalies, showed a significantly higher rate of CMA positive results and of pathogenic CNVs. In the next-generation sequencing era, our study confirms once again the relevant diagnostic output of CMA in patients with IDD, either isolated or associated with other comorbidities. Since more than half of the patients presented brain anomalies in this study, we propose that neuroimaging should be performed in such cases, particularly in the presence of genomic imbalances.

Keywords

synaptopathies - intellectual developmental disorders - autism spectrum disorders - epilepsy - brain anomalies

Authors' Contributions

R.M. and C.C. contributed to conceptualize this study, to investigate, to collect and analyze data, and wrote the draft, under the guidance, supervision, and methodology of R.B. and L.B., who reviewed the article together with A.B., A.N., and G.C. M.G. contributed to methodology, data curation and formal analysis, and created figures. R.P. analyzed patients' neuroimaging. S.G., A.N., and L.B. conducted chromosomal microarray analysis. C.F., V.C., A.G., and T.M. contributed bioinformatics and statistical data.

^* These authors contributed equally to this work.

^† These authors contributed equally as senior investigators.

Publication History

Received: 27 May 2020

Accepted: 27 July 2020

Article published online:
18 September 2020

• References

• 1 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed.. American Psychiatric Association; Washington, DC: 2013
• 2 Greenspan S. Borderline intellectual functioning: an update. Curr Opin Psychiatry 2017; 30 (02) 113-122
• 3 Khan MA, Khan S, Windpassinger C, Badar M, Nawaz Z, Mohammad RM. The molecular genetics of autosomal recessive nonsyndromic intellectual disability: a mutational continuum and future recommendations. Ann Hum Genet 2016; 80 (06) 342-368
• 4 Leonard H, Wen X. The epidemiology of mental retardation: challenges and opportunities in the new millennium. Ment Retard Dev Disabil Res Rev 2002; 8 (03) 117-134
• 5 Polyak A, Rosenfeld JA, Girirajan S. An assessment of sex bias in neurodevelopmental disorders. Genome Med 2015; 7: 94
• 6 Torres F, Barbosa M, Maciel P. Recurrent copy number variations as risk factors for neurodevelopmental disorders: critical overview and analysis of clinical implications. J Med Genet 2016; 53 (02) 73-90
• 7 Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators; Centers for Disease Control and Prevention (CDC). Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill Summ 2014; 63 (02) 1-21
• 8 Schaefer GB, Mendelsohn NJ. Professional Practice and Guidelines Committee. Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions. Genet Med 2013; 15 (05) 399-407
• 9 Thomas P, Guerrini R, Arzimanoglou A. Le epilessie - Diagnosi e trattamento. 2nd ed.. Masson: Elsevier; 2001
• 10 Jeste SS, Tuchman R. Autism spectrum disorder and epilepsy: two sides of the same coin?. J Child Neurol 2015; 30 (14) 1963-1971
• 11 Thomas S, Hovinga ME, Rai D, Lee BK. Brief report: prevalence of co-occurring epilepsy and autism spectrum disorder: the U.S. national survey of children's health 2011-2012. J Autism Dev Disord 2017; 47 (01) 224-229
• 12 Viscidi EW, Triche EW, Pescosolido MF. et al. Clinical characteristics of children with autism spectrum disorder and co-occurring epilepsy. PLoS One 2013; 8 (07) e67797
• 13 Brooks-Kayal AR, Bath KG, Berg AT. et al. Issues related to symptomatic and disease-modifying treatments affecting cognitive and neuropsychiatric comorbidities of epilepsy. Epilepsia 2013; 54 (Suppl. 04) 44-60
• 14 Won H, Mah W, Kim E. Autism spectrum disorder causes, mechanisms, and treatments: focus on neuronal synapses. Front Mol Neurosci 2013; 6: 19
• 15 Miller DT, Adam MP, Aradhya S. et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet 2010; 86 (05) 749-764
• 16 Cooper GM, Coe BP, Girirajan S. et al. A copy number variation morbidity map of developmental delay. Nat Genet 2011; 43 (09) 838-846
• 17 Battaglia A, Doccini V, Bernardini L. et al. Confirmation of chromosomal microarray as a first-tier clinical diagnostic test for individuals with developmental delay, intellectual disability, autism spectrum disorders and dysmorphic features. Eur J Paediatr Neurol 2013; 17 (06) 589-599
• 18 Kariminejad R, Lind-Thomsen A, Tümer Z. et al. High frequency of rare copy number variants affecting functionally related genes in patients with structural brain malformations. Hum Mutat 2011; 32 (12) 1427-1435
• 19 Erbetta A, Bulgheroni S, Contarino VE. et al. Low-functioning autism and nonsyndromic intellectual disability: magnetic resonance imaging (MRI) findings. J Child Neurol 2015; 30 (12) 1658-1663
• 20 Blackmon K. Structural MRI biomarkers of shared pathogenesis in autism spectrum disorder and epilep. Epilep Behav 2015; 47: 172-182
• 21 Murias K, Moir A, Myers KA, Liu I, Wei XC. Systematic review of MRI findings in children with developmental delay or cognitive impairment. Brain Dev 2017; 39 (08) 644-655
• 22 Ecker C. The neuroanatomy of autism spectrum disorder: an overview of structural neuroimaging findings and their translatability to the clinical setting. Autism 2017; 21 (01) 18-28
• 23 van Karnebeek CD, Jansweijer MC, Leenders AG, Offringa M, Hennekam RC. Diagnostic investigations in individuals with mental retardation: a systematic literature review of their usefulness. Eur J Hum Genet 2005; 13 (01) 6-25
• 24 Klein M, van Donkelaar M, Verhoef E, Franke B. Imaging genetics in neurodevelopmental psychopathology. Am J Med Genet B Neuropsychiatr Genet 2017; 174 (05) 485-537
• 25 Barkovich AJ, Guerrini R, Kuzniecky RI, Jackson GD, Dobyns WB. A developmental and genetic classification for malformations of cortical development: update 2012. Brain 2012; 135 (Pt 5): 1348-1369
• 26 Bertholdo D, de Carvalho Neto A, Castillo M. Posterior fossa malformation associated with cerebral anomalies: genetic and imaging features. Top Magn Reson Imaging 2011; 22 (06) 295-302
• 27 Linee Guida Per La Diagnosi Citogenetica 2013. Italy. SIGU (Società Italiana Genetica Umana. Accessed 2018 at: https://www.sigu.net
• 28 MacDonald JR, Ziman R, Yuen RK, Feuk L, Scherer SW. The database of genomic variants: a curated collection of structural variation in the human genome. Nucleic Acids Res. 2013 . Accessed 2018 at: http://dgv.tcag.ca/app/home
• 29 Firth HV. et al. DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans using Ensembl Resources. Am J Hum Genet 2009; 84: 524-533 Accessed 2018 at: https://decipher.sanger.ac.uk/
• 30 National Center for Biotechnology Information (NCBI) [Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; 1988. Accessed 2018 at: http://www.ncbi.nlm.nih.gov/pubmed
• 31 Online Mendelian Inheritance in Man, OMIM^¯. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University (Baltimore, MD). Accessed 2018 at: https://omim.org/
• 32 Stelzer G, Rosen R, Plaschkes I. et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analysis. Current Protocols in Bioinformatics 2016; 54: 1.30.1-1.30.33 Accessed 2018 at: https://www.genecards.org
• 33 Kearney HM, Thorland EC, Brown KK, Quintero-Rivera F, South ST. Working Group of the American College of Medical Genetics Laboratory Quality Assurance Committee. American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants. Genet Med 2011; 13 (07) 680-685
• 34 Silva M, de Leeuw N, Mann K. et al. European guidelines for constitutional cytogenomic analysis. Eur J Hum Genet 2019; 27 (01) 1-16
• 35 Amiet C, Gourfinkel-An I, Bouzamondo A. et al. Epilepsy in autism is associated with intellectual disability and gender: evidence from a meta-analysis. Biol Psychiatry 2008; 64 (07) 577-582
• 36 Díaz-Anzaldúa A, Díaz-Martínez A. Genetic, environmental, and epigenetic contribution to the susceptibility to autism spectrum disorders [in Spanish]. Rev Neurol 2013; 57 (12) 556-568
• 37 Jiang YH, Wang Y, Xiu X, Choy KW, Pursley AN, Cheung SW. Genetic diagnosis of autism spectrum disorders: the opportunity and challenge in the genomics era. Crit Rev Clin Lab Sci 2014; 51 (05) 249-262
• 38 Merikangas AK, Segurado R, Heron EA. et al. The phenotypic manifestations of rare genic CNVs in autism spectrum disorder. Mol Psychiatry 2015; 20 (11) 1366-1372
• 39 Jacquemont S, Coe BP, Hersch M. et al. A higher mutational burden in females supports a “female protective model” in neurodevelopmental disorders. Am J Hum Genet 2014; 94 (03) 415-425
• 40 Capra V, Biancheri R, Morana G. et al. Periventricular nodular heterotopia in Smith-Magenis syndrome. Am J Med Genet A 2014; 164A (12) 3142-3147
• 41 Maya I, Vinkler C, Konen O. et al. Abnormal brain magnetic resonance imaging in two patients with Smith-Magenis syndrome. Am J Med Genet A 2014; 164A [phone]
• 42 Hu J, Liao J, Sathanoori M. et al. CNTN6 copy number variations in 14 patients: a possible candidate gene for neurodevelopmental and neuropsychiatric disorders. J Neurodev Disord 2015; 7 (01) 26
• 43 Jamuar SS, Walsh CA. Genomic variants and variations in malformations of cortical development. Pediatr Clin North Am 2015; 62 (03) 571-585
• 44 Sajan SA, Fernandez L, Nieh SE. et al. Both rare and de novo copy number variants are prevalent in agenesis of the corpus callosum but not in cerebellar hypoplasia or polymicrogyria. PLoS Genet 2013; 9 (10) e1003823
• 45 Bauman ML, Kemper TL. Neuroanatomic observations of the brain in autism: a review and future directions. Int J Dev Neurosci 2005; 23 (2-3): 183-187
• 46 Courchesne E, Campbell K, Solso S. Brain growth across the life span in autism: age-specific changes in anatomical pathology. Brain Res 2011; 1380: 138-145
• 47 DiCicco-Bloom E, Lord C, Zwaigenbaum L. et al. The developmental neurobiology of autism spectrum disorder. J Neurosci 2006; 26 (26) 6897-6906