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VarScan2 analysis of de novo variants in monozygotic twins discordant for schizophrenia.
- Source :
-
Psychiatric genetics [Psychiatr Genet] 2017 Apr; Vol. 27 (2), pp. 62-70. - Publication Year :
- 2017
-
Abstract
- Objectives: Monozygotic twins with near-identical genotypes and discordance for complex diseases represent an exceptional resource to ascertain disease etiology. This strategy has been particularly effective with the availability of high-resolution complete individual genome sequencing. The challenge is using effective approaches to identify relevant differences that may cause or contribute toward disease discordance.<br />Participants and Methods: This study carried out a VarScan2 bioinformatic analysis and a pathway analysis on whole-genome sequences from two sets of monozygotic twins.<br />Results: Variants were identified that were present in the affected twin, but not found in the unaffected twin. Such variations are expected to be de novo and originate during the independent development of the twins and may make them discordant for the disease. The genes and de novo variants identified in this experiment are compatible with their involvement in schizophrenia. Further analysis of the variants identified pathways including glutamate receptor signaling that have been implicated in this neurodevelopmental disease.<br />Conclusion: The results support the polygenic nature of schizophrenia and the threshold model for its development. The results also show the effectiveness of VarScan2 to identify 'the needle in the hay stack' that may cause schizophrenia, specifically in the two patients. It offers a proof of principle for assessment of the genetic etiology of complex disorders where discordance of monozygotic twins is an established phenomenon.
Details
- Language :
- English
- ISSN :
- 1473-5873
- Volume :
- 27
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Psychiatric genetics
- Publication Type :
- Academic Journal
- Accession number :
- 28125460
- Full Text :
- https://doi.org/10.1097/YPG.0000000000000162