| First Author | Shaikh TH | Year | 2011 |
| Journal | Hum Mol Genet | Volume | 20 |
| Issue | 5 | Pages | 880-93 |
| PubMed ID | 21147756 | Mgi Jnum | J:169042 |
| Mgi Id | MGI:4939572 | Doi | 10.1093/hmg/ddq527 |
| Citation | Shaikh TH, et al. (2011) Genes and biological processes commonly disrupted in rare and heterogeneous developmental delay syndromes. Hum Mol Genet 20(5):880-93 |
| abstractText | Rare copy number variations (CNVs) are a recognized cause of common human disease. Predicting the genetic element(s) within a small CNV whose copy number loss or gain underlies a specific phenotype might be achieved reasonably rapidly for single patients. Identifying the biological processes that are commonly disrupted within a large patient cohort which possess larger CNVs, however, requires a more objective approach that exploits genomic resources. In this study, we first identified 98 large, rare CNVs within patients exhibiting multiple congenital anomalies. All patients presented with global developmental delay (DD), while other secondary symptoms such as cardiac defects, craniofacial features and seizures were varyingly presented. By applying a robust statistical procedure that matches patients' clinical phenotypes to laboratory mouse gene knockouts, we were able to strongly implicate anomalies in brain morphology and, separately, in long-term potentiation as manifestations of these DD patients' disorders. These and other significantly enriched model phenotypes provide insights into the pathoetiology of human DD and behavioral and anatomical secondary symptoms that are specific to DD patients. These enrichments set apart 103 genes, from among thousands overlapped by these CNVs, as strong candidates whose copy number change causally underlies approximately 46% of the cohort's DD syndromes and between 59 and 80% of the cohort's secondary symptoms. We also identified significantly enriched model phenotypes among genes overlapped by CNVs in both DD and learning disability cohorts, indicating a congruent etiology. These results demonstrate the high predictive potential of model organism phenotypes when implicating candidate genes for rare genomic disorders. |
