Project description:Our data are useful to expand the molecular spectrum of AUTS2 pathogenic variants and to broaden our knowledge on the clinical phenotype associated.
Project description:Intellectual disability is a common condition that carries lifelong severe medical and developmental consequences. The causes of intellectual disability (ID) remain unknown for the majority of patients due to the extensive clinical and genetic heterogeneity of this disorder. De novo mutations may play an important role in ID as most individuals with ID present as isolated cases without family history and/or clear syndromic indication. In addition, the involvement of such mutations have recently been demonstrated in a small number of individuals with ID. Here we evaluate the diagnostic potential and role of de novo mutations in a cohort of 100 patients with ID of unknown cause using family-based exome sequencing. Single end short-read (50 bp) SOLiD 4 sequencing data for 300 individuals, constituting 100 patient-parent trios. For more details please read; http://www.nejm.org/doi/full/10.1056/NEJMoa1206524. Dataset is created by RUNMC (Radboud University, Nijmegen Medical Center), partner of Geuvadis consortium (http://www.geuvadis.org).
Project description:Targeted next-generation sequencing in children with intellectual disabilities, autism spectrum disorders and multiple congenital abnormalities
Project description:ost adults with intellectual disabilities (ID) do not undergo genetic diagnostic investigation as part of their clinical care and have 'missed the boat' with regard to the WES and WGS genetic testing that is now being provided for children with ID. There is a dramatically increased risk of psychistric disorders in adults with ID, e.g. the risk of psychoses is 10X higher than in the general population. It remains an open question as to how much of adult ID is genetic in origin and how similar the genetic forms of adult ID are to those being diagnosed in children, in part due to survivor bias. There is also the opportunity to identify adults with treatable forms of ID, of which over 80 have been described, thus improving their clinical management. Furthermore, analysis of medical records of adults with genetic forms of ID can help to characterise the 'natural history' of individual disorders, resulting in more accurate prognoses for diagnosed children and identifying opportunities for improved management and possibly therapeutic intervention (e.g. optimal anti-epileptic therapy). Here we propose to exome sequence (to ~50X coverage) 200 adults with ID and co-morbid psychiatric disorders. This cohort has previously been assayed with chromosomal microarrays (Wolfe et al 2017 EJHG, 25, 66–72) identifying a diagnostic yield of ~11% which is comparable to the CNV diagnostic yield in various child ID cohorts (10-15%). The authors observed no substantive biases in diagnostic yield between different psychiatric diagnostic classes. The WES data will be analysed using the diagnostic workflows developed in the DDD study to ensure comparability between child and adult ID datasets. This study is intended as a pilot study to demonstrate the value of WES in adults with ID.
This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
Project description:CNV are known to be a frequent cause of the autism spectrum disorders (ASD) and intellectual disabilities (ID). However, the clinical heterogeneity of both disorders causes the diagnostic efficacy of CNV analysis to be modest. We conclude that comorbidities such as microcephaly, facial dysmorphia and epilepsy increase the risk of the pathogenic CNV finding in patients with ID and ASD. However, the significance of these comorbidities differs between both groups and shows dependency on whether the patients were primarily classified as ID or ASD. We suggest that stratification of the patients according to their comorbidities before testing can increase the yield of the detection rate of pathogenic CNV in both groups. The likelihood of pathogenic CNV detection in ASD patients without any comorbidities is low. Therefore, the effectivity of CNV analysis in these cases is modest
Project description:This analysis includes the whole-genome screening of unbalanced chromosomal rearrangements (copy-number variants; CNV) in a boy with neurodevelopmental disorders and epilepsy.