Autism is a heritable neurodevelopmental disorder with substantial genetic heterogeneity. Studies point to possible links between autism and two serotonin related genes: SLC6A4 and ITGB3 with a sex-specific genetic effect and interaction between the genes. Despite positive findings, inconsistent results have complicated interpretation. This study seeks to validate and clarify previous findings in an independent dataset taking into account sex, family-history (FH) and gene-gene effects. Family-based association analysis was performed within each gene. Gene-gene interactions were tested using extended multifactor dimensionality reduction (EMDR) and MDR-phenomics (MDRP) using sex of affecteds and FH as covariates. No significant associations with individual SNPs were found in the datasets stratified by sex, but associations did emerge when we stratified by family history. While not significant in the overall dataset, nominally significant association was identified at RS2066713 (P=0.006) within SLC6A4 in family-history negative (FH-) families, at RS2066713 (P=0.038) in family-history positive (FH+) families but with the opposite risk allele as in the FH-families. For ITGB3, nominally significant association was identified at RS3809865 overall (P=0.040) and within FH+ families (P=0.031). However, none of the associations survived the multiple testing correction.MDR-Pconfirmed gene-gene effects using sex of affecteds (P=0.023) and family history (P=0.014, survived the multiple testing corrections) as covariates. Our results indicate the extensive heterogeneity within these two genesamongfamilies. The potential interaction between SLC6A4 and ITGB3 maybe clarified using family history as an indicator of genetic architecture, illustrating the importance of covariates as markers of heterogeneity in genetic analyses.
|Original language||English (US)|
|Number of pages||7|
|Journal||American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics|
|State||Published - Mar 2010|
ASJC Scopus subject areas
- Psychiatry and Mental health
- Cellular and Molecular Neuroscience