The significant clinical efficacy of lithium and lamotrigine in the described patients is consistent with the hypothesis that microdeletion of the SHANK3 gene may be associated with bipolar disorder.

The described phenotypes were characterized by intellectual disability, general speech underdevelopment, muscle hypotonia, and developmental dyspraxia. Their causal relationships with epileptic encephalopathy, schizophrenia, bipolar and hyperkinetic disorders have been analyzed.

Prospective studies of two patients with Phelan McDermid syndrome (22q13.3 microdeletions of the SHANK3 gene) within 10-12 years after genome scanning allowed describing the clinical polymorphism of developmental disorders. The sensitivity of psychotic symptoms to antipsychotic and mood stabilizer therapy has also been studied.

Manifest psychotic disorders in patients did not reveal an affinity for therapy with amisulpride, haloperidol, quetiapine, which demonstrated a partial therapeutic response to treatment with aripiprazole, which cast doubt on the possibility of qualifying psychotic symptoms in patients as the debut of schizophrenia. The partial therapeutic efficacy of combination therapy with aripiprazole and benzodiazepines (clonazepam/diazepam) qualified psychotic episodes in two patients with 22q13.3 syndrome as pediatric delirium. The significant clinical efficacy of lithium and lamotrigine in the described patients is consistent with the hypothesis that microdeletion of the SHANK3 gene may be associated with bipolar disorder.

The combination of lithium and lamotrigine may be recommended for the treatment of polymorbid mental disorders in patients with ASD and 22q13.3 syndrome. If lithium salts are poorly tolerated, a combination of lamotrigine and aripiprazole may be used to treat polymorbid mental disorders with confusion and catatonic symptoms in ASD.

No significant relationships.

It is well known that between two thirds and three fourths of children with autism also have intellectual disability. Some of these children were not diagnosed as to have autism due to diagnostic overshadowing between autism and severe forms of intellectual disability.

The objective of this research was to determine the capability of autism index (AI) to correctly identify individuals who have been already diagnosed as having autism.

The sample consisted of 64 participants with moderate, severe and profound intellectual disabilities who have been previously determined to meet DSM-IV-TR criteria for autism spectrum disorder. Autism index was derived by Gilliam Autism Rating Scale (GARS-2).

It was revealed that AI was very high in 39 (60.9%) participants meaning that they were very likely to have autism according to GARS-2. In addition, probability of autism in 18 (28.1%) participants was labeled as “possibly”. AI failed to detect 7 children with autism spectrum disorders.

Sensitivity of AI is quite acceptable (88.9%) providing all children with scores higher than 69 (possibly and very likely as having autism) are considered to have autism spectrum disorder.

Autism spectrum disorder (ASD) was once considered to be highly associated with intellectual disability and to show a characteristic IQ profile, with strengths in performance over verbal abilities and a distinctive pattern of ‘peaks’ and ‘troughs’ at the subtest level. However, there are few data from epidemiological studies.

Comprehensive clinical assessments were conducted with 156 children aged 10–14 years [mean (s.d.)=11.7 (0.9)], seen as part of an epidemiological study (81 childhood autism, 75 other ASD). A sample weighting procedure enabled us to estimate characteristics of the total ASD population.

Of the 75 children with ASD, 55% had an intellectual disability (IQ<70) but only 16% had moderate to severe intellectual disability (IQ<50); 28% had average intelligence (115>IQ>85) but only 3% were of above average intelligence (IQ>115). There was some evidence for a clinically significant Performance/Verbal IQ (PIQ/VIQ) discrepancy but discrepant verbal versus performance skills were not associated with a particular pattern of symptoms, as has been reported previously. There was mixed evidence of a characteristic subtest profile: whereas some previously reported patterns were supported (e.g. poor Comprehension), others were not (e.g. no ‘peak’ in Block Design). Adaptive skills were significantly lower than IQ and were associated with severity of early social impairment and also IQ.

In this epidemiological sample, ASD was less strongly associated with intellectual disability than traditionally held and there was only limited evidence of a distinctive IQ profile. Adaptive outcome was significantly impaired even for those children of average intelligence.

Calendar calculation is the ability to quickly name the day that a given date falls on. Previous research has suggested that savant calendar calculation is based on rote memory and the use of rule-based arithmetic skills. The objective of this study was to identify the cognitive processes that distinguish calendar calculation in savant individuals from healthy calendar calculators.

Savant calendar calculators with autism (ACC, n=3), healthy calendar calculators (HCC, n=3), non-savant subjects with autism (n=6) and healthy calendar calculator laymen (n=18) were included in the study. All participants calculated dates of the present (current month). In addition, ACC and HCC also calculated dates of the past and future 50 years.

ACC showed shorter reaction times and fewer errors than HCC and non-savant subjects with autism, and significantly fewer errors than healthy calendar calculator laymen when calculating dates of the present. Moreover, ACC performed faster and more accurate than HCC regarding past dates. However, no differences between ACC and HCC were detected for future date calculation.

The findings may imply distinct calendar calculation strategies in ACC and HCC, with HCC relying on calendar regularities for all types of dates and an involvement of (rote) memory in ACC when processing dates of the past and the present.