Autism and the related disorders Asperger Syndrome (AS) and Pervasive Developmental Disorder Not Otherwise Specified (PDDNOS) are characterised by qualitative impairments of social interaction and communication, and restricted and repetitive patterns of behaviour of early childhood onset. They are now widely accepted as forming a spectrum of disorders, the so-called autism spectrum of conditions (ASCs), with the term 'spectrum' indicating the variation in the clinical phenotype observed [1
]. Twin and family studies have demonstrated the etiological role of a number of genes [2
], and linkage and association studies have begun to converge on regions of susceptibility and possible candidate genes respectively (reviewed in [5
Unfortunately, however, the genetic research has been plagued with a failure to replicate findings, and with regions of linkage seemingly occurring on the majority of chromosomes. Recent research has taken two different approaches to address this. First, pooling data to increase sample sizes, such as with the Autism Genetic Resource Exchange [6
] database, and secondly, examining subgroups within the autism spectrum, such as language delayed groups, those exhibiting repetitive patterns of behaviour and those meeting the more specific criteria for AS.
This latter approach is predicated on a model in which the spectrum is not a unitary concept, but, instead, consists of subgroups with unique but overlapping genetic influences [7
]. At its most basic level this model argues that different sets of genes are responsible for the social, communication and behavioural impairments respectively. In support of this, the twin study of Ronald et al. 2006 [8
] identified low phenotypic correlations between the three subscales of social interaction, communication and restricted/repetitive patterns of behaviour. There is also some genetic evidence to support this model. Shao [9
], demonstrated improved linkage signals on chromosome 15q for a 'restricted and repetitive' behavioural subgroup, consistent with genes contributing differentially to these phenotypic characteristics. Although the genetic studies of Bradford et al. [10
] and Buxbaum et al. [11
] appear to also support this model, by considering language delay these studies have simply stratified their samples according to a general cognitive characteristic.
In contrast, however, other researchers have argued for a severity gradient [12
], with presentation being modified according to the severity of autism symptoms. However, even if a severity gradient is the correct model it is still unclear whether this represents variation in severity of the core phenotype per se
, or is a reflection of another factor, such as the impact of cognitive function on the expression of the phenotype.
There are a number of considerations that might explain the discrepancies between studies. An important consideration is the design of the studies. For example, Spiker's and Silverman's examined clustering according to the Autism Diagnostic Interview (ADI-R), whilst Constantino's [13
] examined clustering on the Social Reciprocity Scale (SRS) and Ronald's [8
] examined multivariate model fitting according to Childhood Asperger Syndrome Test (CAST). Clearly all questionnaires differ, as some are designed as screening instruments whilst others are aimed at diagnosis, some are concerned with higher functioning individuals whilst others are interested in a wider range of disability and some are self-report whilst others are informant-based. Other differences between studies included whether multiplex families or singletons were investigated, the sample sizes and the cognitive range of subjects included. All of these factors may have influenced the results.
In this current study, adult singletons with higher functioning ASCs are examined for their clustering on the fifty clinical features examined in the Autism Spectrum Quotient [14
], a screening questionnaire used in the diagnosis of higher functioning ASCs. In contrast to previous studies we have used the AQ and have made no a priori
assumptions about the underlying factor structure of this questionnaire and the clinical features it identifies. Our aim was to examine the possible clustering of responses within our study population and to determine whether the data obtained supported either a severity or a subgroup model to account for the phenotypic variation observed within the ASCs. Previous studies have sampled children with ASCs, but this is the first to examine an adult sample in this way. There is evidence that for a significant minority the ASC symptoms improve with age [15
], suggesting that there may be different subgroups within this population, and raising the possibility that a different pattern of clustering will be observed among the adult ASC population. In addition, by including only those with higher functioning ASCs the effects of cognitive impairment per se
on clustering are relatively reduced.