|Application:||40980, Rare deleterious CNVs share some overlapping effects on brain structure.|
|Title:||CNV calls using PennCNV and QuantiSNP|
|Archived:||14 Jan 2021|
|Personal:||Contains individual-level data|
Return is not presently available
We have called CNVs in the full UK Biobank 488,295 samples/individuals that passed our quality control on the number of SNPs. The matrix of all samples, SNPs, BAF, LRR, and confidential scores were downloaded in 2018. The calls of CNVs were performed with two tools PennCNV and QuantiSNP. The pipeline implementation on HPC and tool versions are detailed in our laboratory GitHub repository https://github.com/labjacquemont/MIND-GENESPARALLELCNV .
Rare deleterious CNVs share some overlapping effects on brain structure.
Neurodevelopmental disorders (NDs) include intellectual disabilities, severe learning disabilities, autism spectrum disorder (ASD) are frequent with a prevalence of 1%, 6%, and 1,4% respectively. They represent a significant health burden with handicaps present throughout life. The genetic contribution to NDs is as high as 80%. With the routine implementation of genetic testing in the neurodevelopmental clinic, rare mutations that contribute significantly to neurodevelopmental symptoms are identified in 10 to 20 % of children with NDs.
However, for most "pathogenic" mutations reported back to patients, we have little or no data to estimate their quantitative impact on neurodevelopment. It is therefore difficult for clinicians to estimate the extent to which a genetic variant may contribute to the neurodevelopmental symptoms in a patient. This is due to 2 major issue: 1) Over 75% of "pathogenic" mutations are very rare and observed only once or a few times in patients. It is therefore impossible to conduct individual association studies and 2) Most studies have focussed on associating mutations with complex categorical diagnoses such as ASD or intellectual disabilities. The cognitive mechanisms underlying these associations remain unknown.
To address this issue of undocumented mutations, we propose a novel strategy to understand the effects of CNVs genome-wide, on cognitive and brain measures involved in neurodevelopmental disorders.
The deliverables are algorithms estimating the effect size of any CNV or SNV on cognitive and behavioral traits assessed along a continuum. This will, allow clinicians to estimate the level of contribution of one or several rare mutations to the neurodevelopmental symptoms in a given patient. It will also provide insight into the mechanisms by which mutations may lead to neurodevelopmental disorders.
|Lead investigator:||Professor Sebastien Jacquemont|
|Lead institution:||CHU Sainte-Justine Research Center|