Páll Magnússon

Rare chromosomal deletions and duplications in attention-deficit hyperactivity disorder: a genome-wide analysis

Shade matching should not only be carried out in daylight conditions but under other light sources.

Prevalence of Autism in Iceland

This clinic-based study estimated the prevalence of autism in Iceland in two consecutive birth cohorts, subjects born in 1974-1983 and in 1984-1993. In the older cohort classification was based on the ICD-9 in 72% of cases while in the younger cohort 89% of cases were classified according to the ICD-10. Estimated prevalence rates for Infantile autism/Childhood autism were 3.8 per 10,000 in the older cohort and 8.6 per 10,000 in the younger cohort. The characteristics of the autistic groups are presented in terms of level of intelligence, male:female ratio, and age at diagnosis. For the younger cohort scores on the Autism Diagnostic Interview-Revised and the Childhood Autism Rating Scale are reported as well. Results are compared with a previous Icelandic study and recent population-based studies in other countries based on the ICD-10 classification system. Methodological issues are discussed as well as implications for future research and service delivery.

Autism Diagnostic Interview-Revised and the Childhood Autism Rating Scale: convergence and discrepancy in diagnosing autism.

The agreement between the Autism Diagnostic Interview–Revised (ADI-R) and the Childhood Autism Rating Scale (CARS) was investigated in the diagnostic assessment of 54 children aged 22–114 months referred for possible autism. The observed agreement between the two systems was 66.7% (Cohens kappa = .40) when the ADI-R definition for autism was applied (i.e., scores reaching cutoff in three domains on the ADI-R), but increased considerably with less stringent criteria; that is, scores reaching cutoffs in two domains and in one domain on the ADI-R. As predicted, the CARS identified more cases of autism than the ADI-R. Children classified as autistic according to both instruments had significantly lower IQ/DQ and more severe autistic symptomatology than those classified with the CARS only.

Validity of self-report and informant rating scales of adult ADHD symptoms in comparison with a semistructured diagnostic interview.

In a study of ADHD symptoms in the relatives of probands diagnosed with ADHD, the validity of self-reported and informant-reported symptoms in childhood and adulthood was investigated with a semistructured diagnostic interview, the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS) adapted for adults, as a criterion. The participating relatives were 80 women and 46 men aged 17 to 77. Rating scales based on the Diagnostic and Statistical Manual of Mental Disorders (4th ed.) were completed by participants and informants. Internal consistency of the scales and interrater reliabilities of the diagnostic interview were satisfactory. Correlations between ratings across sources of information supported convergent and divergent validity. Self-report scales and informant scales predicted interview-based diagnoses in childhood and adulthood with adequate sensitivities and specificities. It was concluded that the rating scales have good psychometric properties, at least in at-risk populations.

Prevalence of autism spectrum disorders in an Icelandic birth cohort

Objectives A steady increase in the prevalence of autism spectrum disorders (ASD) has been reported in studies based on different methods, requiring adjustment for participation and missing data. Recent studies with high ASD prevalence rates rarely report on co-occurring medical conditions. The aim of the study was to describe the prevalence of clinically confirmed cases of ASD in Iceland and concomitant medical conditions. Design The cohort is based on a nationwide database on ASD among children born during 1994–1998. Participants A total of 267 children were diagnosed with ASD, 197 boys and 70 girls. Only clinically confirmed cases were included. All received physical and neurological examination, standardised diagnostic workup for ASD, as well as cognitive testing. ASD diagnosis was established by interdisciplinary teams. Information on medical conditions and chromosomal testing was obtained by record linkage with hospital registers. Setting Two tertiary institutions in Iceland. The population registry recorded 22u2005229 children in the birth cohort. Results Prevalence of all ASD was 120.1/10u2005000 (95% CI 106.6 to 135.3), for boys 172.4/10u2005000 (95% CI 150.1 to 198.0) and for girls 64.8/10u2005000 (95% CI 51.3 to 81.8). Prevalence of all medical conditions was 17.2% (95% CI 13.2 to 22.2), including epilepsy of 7.1% (95% CI 4.6 to 10.8). The proportion of ASD cases with cognitive impairment (intellectual quotient <70) was 45.3%, but only 34.1% were diagnosed with intellectual disability (ID). Children diagnosed earlier or later did not differ on mean total score on a standardised interview for autism. Conclusions The number of clinically verified cases is larger than in previous studies, yielding a prevalence of ASD on a similar level as found in recent non-clinical studies. The prevalence of co-occurring medical conditions was high, considering the low proportion of ASD cases that also had ID. Earlier detection is clearly desirable in order to provide counselling and treatment.

Prevalence of autism in an urban population of adults with severe intellectual disabilities – a preliminary study

BACKGROUNDnResearch on the prevalence of autism in Iceland has indicated that one possible explanation of fewer autism cases in older age groups was due to an underestimation of autism in individuals with intellectual disabilities (IDs). The present study systematically searched for autism cases in the adult population of individuals with severe ID living in the city of Reykjavik, Iceland.nnnMETHODSnPotential participants (n = 256) were recruited through the Regional Office for the Affairs of the Handicapped in Reykjavik. First, a screening tool for autism was applied, followed by the Childhood Autism Rating Scale and finally the Autism Diagnostic Interview-Revised (ADI-R).nnnRESULTSnThe point prevalence of severe ID was 3.7/1000 (95% CI 3.2-4.1) with a male-female ratio of 1.2:1. Participation rate in the study was 46.5%. Participants were younger than non-participants and more often residents of group homes. The prevalence of autism was 21% (25/119) (95% CI 14.7-29.2) with a male-female ratio of 1.8:1. Of the individuals with autism, 10/25 (40%) were verbal according to the ADI-R definition, and 18/25 (72%) had active epilepsy and/or other neurological conditions and handicaps.nnnCONCLUSIONnThe study identified twice the number of autism cases than those previously recognised within the service system. Autism is a prevalent additional handicap in individuals with severe ID, which should always be considered in this population. There are indications that the estimated prevalence of autism found should be considered minimal.

No association between a common single nucleotide polymorphism, rs4141463, in the MACROD2 gene and autism spectrum disorder†

The Autism Genome Project (AGP) Consortium recently reported genome‐wide significant association between autism and an intronic single nucleotide polymorphism marker, rs4141463, within the MACROD2 gene. In the present study we attempted to replicate this finding using an independent case–control design of 1,170 cases with autism spectrum disorder (ASD) (874 of which fulfilled narrow criteria for Autism (A)) from five centers within Europe (UK, Germany, the Netherlands, Italy, and Iceland), and 35,307 controls. The combined sample size gave us a non‐centrality parameter (NCP) of 11.9, with 93% power to detect allelic association of rs4141463 at an alpha of 0.05 with odds ratio of 0.84 (the best odds ratio estimate of the AGP Consortium data), and for the narrow diagnosis of autism, an NCP of 8.9 and power of 85%. Our case–control data were analyzed for association, stratified by each center, and the summary statistics were combined using the meta‐analysis program, GWAMA. This resulted in an odds ratio (OR) of 1.03 (95% CI 0.944–1.133), with a P‐value of 0.5 for ASD and OR of 0.99 (95% CI 0.88–1.11) with P‐valueu2009=u20090.85 for the Autism (A) sub‐group. Therefore, this study does not provide support for the reported association between rs4141463 and autism.

Electroencephalography as a clinical tool for diagnosing and monitoring attention deficit hyperactivity disorder: a cross-sectional study

Objectives The aim of this study was to develop and test, for the first time, a multivariate diagnostic classifier of attention deficit hyperactivity disorder (ADHD) based on EEG coherence measures and chronological age. Setting The participants were recruited in two specialised centres and three schools in Reykjavik. Participants The data are from a large cross-sectional cohort of 310 patients with ADHD and 351 controls, covering an age range from 5.8 to 14u2005years. ADHD was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders fourth edition (DSM-IV) criteria using the K-SADS-PL semistructured interview. Participants in the control group were reported to be free of any mental or developmental disorders by their parents and had a score of less than 1.5 SDs above the age-appropriate norm on the ADHD Rating Scale-IV. Other than moderate or severe intellectual disability, no additional exclusion criteria were applied in order that the cohort reflected the typical cross section of patients with ADHD. Results Diagnostic classifiers were developed using statistical pattern recognition for the entire age range and for specific age ranges and were tested using cross-validation and by application to a separate cohort of recordings not used in the development process. The age-specific classification approach was more accurate (76% accuracy in the independent test cohort; 81% cross-validation accuracy) than the age-independent version (76%; 73%). Chronological age was found to be an important classification feature. Conclusions The novel application of EEG-based classification methods presented here can offer significant benefit to the clinician by improving both the accuracy of initial diagnosis and ongoing monitoring of children and adolescents with ADHD. The most accurate possible diagnosis at a single point in time can be obtained by the age-specific classifiers, but the age-independent classifiers are also useful as they enable longitudinal monitoring of brain function.