Unknown

Dataset Information

0

Loss-of-function variants in schizophrenia risk and SETD1A as a candidate susceptibility gene.


ABSTRACT: Loss-of-function (LOF) (i.e., nonsense, splice site, and frameshift) variants that lead to disruption of gene function are likely to contribute to the etiology of neuropsychiatric disorders. Here, we perform a systematic investigation of the role of both de novo and inherited LOF variants in schizophrenia using exome sequencing data from 231 case and 34 control trios. We identify two de novo LOF variants in the SETD1A gene, which encodes a subunit of histone methyltransferase, a finding unlikely to have occurred by chance, and provide evidence for a more general role of chromatin regulators in schizophrenia risk. Transmission pattern analyses reveal that LOF variants are more likely to be transmitted to affected individuals than controls. This is especially true for private LOF variants in genes intolerant to functional genetic variation. These findings highlight the contribution of LOF mutations to the genetic architecture of schizophrenia and provide important insights into disease pathogenesis.

SUBMITTER: Takata A 

PROVIDER: S-EPMC4387883 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

Loss-of-function variants in schizophrenia risk and SETD1A as a candidate susceptibility gene.

Takata Atsushi A   Xu Bin B   Ionita-Laza Iuliana I   Roos J Louw JL   Gogos Joseph A JA   Karayiorgou Maria M  

Neuron 20140501 4


Loss-of-function (LOF) (i.e., nonsense, splice site, and frameshift) variants that lead to disruption of gene function are likely to contribute to the etiology of neuropsychiatric disorders. Here, we perform a systematic investigation of the role of both de novo and inherited LOF variants in schizophrenia using exome sequencing data from 231 case and 34 control trios. We identify two de novo LOF variants in the SETD1A gene, which encodes a subunit of histone methyltransferase, a finding unlikely  ...[more]

Similar Datasets

| S-EPMC6689268 | biostudies-literature
| S-EPMC4490285 | biostudies-literature
| S-EPMC6283057 | biostudies-literature
2020-08-20 | GSE143666 | GEO
| S-EPMC7212671 | biostudies-literature
| S-EPMC3824289 | biostudies-literature
| S-EPMC8592033 | biostudies-literature
| S-EPMC4393692 | biostudies-literature
| S-EPMC5217615 | biostudies-literature