21339
Association of Dysfunctional Polymorphisms in Acetylserotonin O-Methyltransferase with Insomnia in ASD
Objectives: To examine the hypothesis that polymorphisms in the ASMT gene are associated with insomnia in ASD.
Methods: We genotyped three known risk SNPs (rs44469096, rs5989681, rs6644635) shown to relate to reduced expression of the ASMT gene. SNPs were genotyped in 120 children (ages 2-13 years) diagnosed with ASD whose parents had completed the Children’s Sleep Habits Questionnaire (CSHQ). These individuals were enrolled in research studies related to sleep in children with ASD, as well as broader autism genetics studies. We initially examined associations of genotypes at each SNP and presence of an insomnia-related problem as indicated by the parent. We additionally evaluated the associations of genotypes at each SNP with sleep onset delay, night wakings, and sleep duration (estimated from parent-reported bedtimes and wake times) to refine the potential relationship of SNPs in ASMT with symptoms of insomnia.
Results: There were 84 children with ASD whose parent indicated a problem in an insomnia-related question on the CSHQ and 36 children with no insomnia-related problems reported. There were no associations between the dysfunctional SNPs genotyped in ASMT and presence of a problem in an insomnia-related domain, however genotypes in rs6644635 were trending toward significance (p=0.058). Upon further examination of specific CSHQ questions, SNP rs6644635 was associated with shorter sleep duration (β= -14.74, p=0.032), and, interestingly, fewer problems with night wakings (OR=0.43, p=0.027). No SNPs were associated with sleep onset delay problems in this dataset (p≥0.238).
Conclusions: The presence of dysfunctional alleles at SNP rs6644635, in the 5’-UTR of the ASMT gene, was associated with short sleep duration. The lack of association of SNP rs6644635 with sleep onset delay and the paradoxical finding of fewer reported problems with night wakings require further examination, including studies that also assess SNPs in genes involved in the metabolism of melatonin (e.g., CYP1A2). Examination of melatonin pathway genes in larger datasets appears warranted.