bioRxivNeurosciencePreprint
ASD Diagnosis in Adults: Phenotype and Genotype Findings from a Clinically-derived Cohort
Jack F. G. UnderwoodiD, Kimberley Marie KendalliD, Jennifer Berrett, Richard AnneyiD, Marianne B. M. van den BreeiD, Jérémy HalliD
Abstract
BackgroundThe last decade has seen the development of services for adults presenting with symptoms of autism spectrum disorder (ASD) in the UK. Compared to children, little is known about the phenotypic and genetic characteristics of these patients.\n\nAimsThis e-cohort study aimed to examine the phenotypic and genetic characteristics of a clinically-presenting sample of adults diagnosed with ASD by specialist services.\n\nMethodsIndividuals diagnosed with ASD as adults were recruited by the National Centre for Mental Health and completed self-report questionnaires, interviews and provided DNA. 105 eligible individuals were matched to 76 healthy controls. We investigated the demographics, social history, comorbid psychiatric and physical disorders. Samples were genotyped, copy number variants (CNVs) were called and polygenic risk scores calculated.\n\nResults89.5% of individuals with ASD had at least one comorbid psychiatric diagnosis with comorbid depression (62.9%) and anxiety (55.2%) the most common. The ASD group experienced more neurological comorbidities than healthy controls, particularly migraine headache. They were less likely to have married or be in work and had more alcohol-related problems. There was a significantly higher load of autism common genetic variants in the adult ASD group compared to controls, but there was no difference in the rate of rare CNVs.\n\nConclusionsThis study provides important information about psychiatric comorbidity in adult ASD which may be used to inform clinical practice and patient counselling. It also suggests that the polygenic load of common ASD-associated variants may be important in conferring risk within non-intellectually disabled population of adults with ASD.
- organism: human
- assay: DNA methylation
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
- Citations
- 2
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