Principal Investigator: Professor Jinchen Li
Department: Central South UniversityTags: 61446, Autism, candidate gene, de novo mutation, GWAS, modifier, penetrance
ASD is an early-onset neurodevelopmental disorder with a global prevalence of 1%, which is clinically characterized by reduced social interactions, impaired communications, and stereotypic and repetitive behavior with different degrees of severity. Moreover, genetic epidemiology studies have indicated that ASD have a high heritability (80%-90%), suggesting that genetic factors may explain most of the risk for ASD, but known autism-causing genes can only explain a small number of patients.
Recently, the result of large-scale sequencing studies in the general population show that an amount of normal control who did not have significantly clinical manifestations of autism also carry damaging variants, especially loss-of-function (LOF) variants. So the reality is that some individuals carry damaging variants can also be healthy and suggest that genetic modifiers that lead to phenotypic variability and changes in penetrance through gene-gene interaction may exist. We hypothesized that the people with disease-causing variants in autism-related genes are protected by other unknown genetic variations in the genome, that is, the genetic modifiers. These genetic modifiers may reduce the penetrance, expressivity, severity of a phenotype and thus have protective effects. Therefore, we would like to use the genetic data from UK Biobank to identify the genetic modifiers of autism related genes in the general population.
By comprehensively analyzing all the variants from the general population genome in UK Biobank, we will find some genetic modifiers of autism related genes, especially some SNPs that may have some protective effect in the general population. These genetic modifiers are expected to help us better understanding of the relationship of phenotype and genotype underlying autism and therefore to greater accuracy for phenotypic predictions. Furthermore, further analysis of genetic modifiers holds great promise to facilitate better diagnosis and prognosis of disease progression, but also to provide direction to its potential therapeutics. In conclusion, this project may be foster the development of personalized treatment strategies based on molecular diagnosis.
We anticipate the project duration to be 36 months.