Browsing by Author "Turinsky, Andrei L"

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    Bluejay 1.0: genome browsing and comparison with rich customization provision and dynamic resource linking
    (BioMed Central, 2008) Soh, Jung; Gordon, Paul M. K.; Taschuk, Morgan L.; Dong, Anguo; Ah-Seng, Andrew C.; Turinsky, Andrei L; Sensen, Christoph W.
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    Obsessive-compulsive disorder and attention-deficit/hyperactivity disorder: distinct associations with DNA methylation and genetic variation
    (2020-08-16) Goodman, Sarah J; Burton, Christie L; Butcher, Darci T; Siu, Michelle T; Lemire, Mathieu; Chater-Diehl, Eric; Turinsky, Andrei L; Brudno, Michael; Soreni, Noam; Rosenberg, David; Fitzgerald, Kate D; Hanna, Gregory L; Anagnostou, Evdokia; Arnold, Paul D; Crosbie, Jennifer; Schachar, Russell; Weksberg, Rosanna
    Abstract Background A growing body of research has demonstrated associations between specific neurodevelopmental disorders and variation in DNA methylation (DNAm), implicating this molecular mark as a possible contributor to the molecular etiology of these disorders and/or as a novel disease biomarker. Furthermore, genetic risk variants of neurodevelopmental disorders have been found to be enriched at loci associated with DNAm patterns, referred to as methylation quantitative trait loci (mQTLs). Methods We conducted two epigenome-wide association studies in individuals with attention-deficit/hyperactivity disorder (ADHD) or obsessive-compulsive disorder (OCD) (aged 4–18 years) using DNA extracted from saliva. DNAm data generated on the Illumina Human Methylation 450 K array were used to examine the interaction between genetic variation and DNAm patterns associated with these disorders. Results Using linear regression followed by principal component analysis, individuals with the most endorsed symptoms of ADHD or OCD were found to have significantly more distinct DNAm patterns from controls, as compared to all cases. This suggested that the phenotypic heterogeneity of these disorders is reflected in altered DNAm at specific sites. Further investigations of the DNAm sites associated with each disorder revealed that despite little overlap of these DNAm sites across the two disorders, both disorders were significantly enriched for mQTLs within our sample. Conclusions Our DNAm data provide insights into the regulatory changes associated with genetic variation, highlighting their potential utility both in directing GWAS and in elucidating the pathophysiology of neurodevelopmental disorders.