Prevalence of autism spectrum disorder phenomenology in genetic disorders: a systematic review and meta-analysis

Background Autism spectrum disorder (ASD) phenomenology is reported to be more common in individuals with some genetic syndromes than in the general population; however, no meta-analysis has provided prevalence data within and between syndromes. In this systematic review and meta-analysis, we aimed to synthesise data from a wide range of papers to provide accurate estimates about ASD phenomenology in genetic and metabolic syndromes. Methods We identified syndromes reported as most likely to be associated with ASD. We searched Ovid PsycINFO, Ovid MEDLINE, Ovid Embase, and PubMed Central for English-language papers published from database creation up to early 2014 with use of syndrome-specific keywords and a set of ASD keywords. We screened and extracted papers that had ASD prevalence data for ten or more people within a genetic syndrome. With use of a prespecified set of reliable criteria, we applied quality weighting to papers and estimated a quality-effects prevalence of ASD phenomenology for each syndrome. We then calculated relative risks to compare ASD between all syndromes and also calculated odds ratios to compare prevalence with the general population taking the current estimate of one in 68 people. Results We identified 168 papers reporting the prevalence of ASD phenomenology and found widely varying methods and quality of data. Quality-weighted effect prevalence estimates of ASD phenomenology were established for Rett's syndrome (female individuals only 61%), Cohen's syndrome (54%), Cornelia de Lange syndrome (43%), tuberous sclerosis complex (36%), Angelman's syndrome (34%), CHARGE syndrome (30%), fragile X syndrome (male individuals only 30%; mixed sex 22%), neurofibromatosis type 1 (18%), Down's syndrome (16%), Noonan's syndrome (15%), Williams' syndrome (12%), and 22q11.2 deletion syndrome (11%). Relative risks and the odds ratio compared with the general population were highest for Rett's syndrome and Cohen's syndrome. In all syndromes, odds ratios showed ASD phenomenology to be significantly more likely than in the general population. Interpretation ASD phenomenology varied between syndromes, but was consistently more likely than in the general population. Further research is needed in these populations, including how ASD in genetic and metabolic syndromes differs from idiopathic autism and what that can tell us about the mechanisms underlying ASD.