Dataset Information

Dissecting the clinical heterogeneity of autism spectrum disorders through defined genotypes.

ABSTRACT: BACKGROUND: The etiology of autism spectrum disorders (ASD) is largely determined by different genetic factors of variable impact. This genetic heterogeneity could be a factor to explain the clinical heterogeneity of autism spectrum disorders. Here, a first attempt is made to assess whether genetically more homogeneous ASD groups are associated with decreased phenotypic heterogeneity with respect to their autistic symptom profile. METHODOLOGY: The autistic phenotypes of ASD subjects with 22q11 deletion syndrome (22q11DS) and ASD subjects with Klinefelter Syndrome (KS) were statistically compared to the symptom profile of a large (genetically) heterogeneous ASD sample. Autism diagnostic interview-revised (ADI-R) variables were entered in different statistical analyses to assess differences in symptom homogeneity and the feasibility of discrimination of group-specific ASD-symptom profiles. PRINCIPAL FINDINGS: The results showed substantially higher symptom homogeneity in both the genetic disorder ASD groups in comparison to the heterogeneous ASD sample. In addition, a robust discrimination between 22q11-ASD and KS-ASD and idiopathic ASD phenotypes was feasible on the basis of a reduced number of autistic scales and symptoms. The lack of overlap in discriminating subscales and symptoms between KS-ASD and 22q11DS-ASD suggests that their autistic symptom profiles cluster around different points in the total diagnostic space of profiles present in the general ASD population. CONCLUSION: The findings of the current study indicate that the clinical heterogeneity of ASDs may be reduced when subgroups based on a specific genotype are extracted from the idiopathic ASD population. The current strategy involving the widely used ADI-R offers a relatively straightforward possibility for assessing genotype-phenotype ASD relationships. Reverse phenotype strategies are becoming more feasible, given the accumulating evidence for the existence of genetic variants of large effect in a substantial proportion of the ASD population.

SUBMITTER: Bruining H

PROVIDER: S-EPMC2878316 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dissecting the clinical heterogeneity of autism spectrum disorders through defined genotypes.

Bruining Hilgo H de Sonneville Leo L Swaab Hanna H de Jonge Maretha M Kas Martien M van Engeland Herman H Vorstman Jacob J

PloS one 20100528 5

<h4>Background</h4>The etiology of autism spectrum disorders (ASD) is largely determined by different genetic factors of variable impact. This genetic heterogeneity could be a factor to explain the clinical heterogeneity of autism spectrum disorders. Here, a first attempt is made to assess whether genetically more homogeneous ASD groups are associated with decreased phenotypic heterogeneity with respect to their autistic symptom profile.<h4>Methodology</h4>The autistic phenotypes of ASD subjects ...[more]

PMID: 20526357

Similar Datasets

Project description:Autism spectrum disorder (ASD) encompasses a group of neurodevelopmental conditions diagnosed solely on the basis of behavioral assessments that reveal social deficits. Progress has been made in understanding its genetic underpinnings, but most ASD-associated genetic variants, which include copy number variants (CNVs) and mutations in ASD-risk genes, account for no more than 1 % of ASD cases. This high level of genetic heterogeneity leads to challenges obtaining and interpreting genetic testing in clinical settings. The traditional definition of syndromic ASD is a disorder with a clinically defined pattern of somatic abnormalities and a neurobehavioral phenotype that may include ASD. Most have a known genetic cause. Examples include fragile X syndrome and tuberous sclerosis complex. We propose dividing syndromic autism into the following two groups: (i) ASD that occurs in the context of a clinically defined syndrome-recognizing these disorders depends on the familiarity of the clinician with the features of the syndrome, and the diagnosis is typically confirmed by targeted genetic testing (eg, mutation screening of FMR1); (ii) ASD that occurs as a feature of a molecularly defined syndrome-for this group of patients, ASD-associated variants are identified by genome-wide testing that is not hypothesis driven (eg, microarray, whole exome sequencing). These ASD groups cannot be easily clinically defined because patients with a given variant have variable somatic abnormalities (dysmorphism and birth defects). In this article, we review common diagnoses from the above categories and suggest a testing strategy for patients, guided by determining whether the individual has essential or complex ASD; patients in the latter group have multiple morphologic anomalies on physical examination. Finally, we recommend that the syndromic versus nonsyndromic designation ultimately be replaced by classification of ASD according to its genetic etiology, which will inform about the associated spectrum and penetrance of neurobehavioral and somatic manifestations.

Project description:BackgroundHeterogeneity in the phenotypic presentation of autism spectrum disorder (ASD) is apparent in the profile and the severity of sensory features. Here, we applied factor mixture modelling (FMM) to test a multidimensional factor model of sensory processing in ASD. We aimed to identify homogeneous sensory subgroups in ASD that differ intrinsically in their severity along continuous factor scores. We also investigated sensory subgroups in relation to clinical variables: sex, age, IQ, social-communication symptoms, restricted and repetitive behaviours, adaptive functioning and symptoms of anxiety and attention-deficit/hyperactivity disorder.MethodsThree hundred thirty-two children and adults with ASD between the ages of 6 and 30 years with IQs varying between 40 and 148 were included. First, three different confirmatory factor models were fit to the 38 items of the Short Sensory Profile (SSP). Then, latent class models (with two-to-six subgroups) were evaluated. The best performing factor model, the 7-factor structure, was subsequently used in two FMMs that varied in the number of subgroups: a two-subgroup, seven-factor model and a three-subgroup and seven-factor model.ResultsThe 'three-subgroup/seven-factor' FMM was superior to all other models based on different fit criteria. Identified subgroups differed in sensory severity from severe, moderate to low. Accounting for the potential confounding effects of age and IQ, participants in these sensory subgroups had different levels of social-communicative symptoms, restricted and repetitive behaviours, adaptive functioning skills and symptoms of inattention and anxiety.LimitationsResults were derived using a single parent-report measure of sensory features, the SSP, which limits the generalisability of findings.ConclusionSensory features can be best described by three homogeneous sensory subgroups that differ in sensory severity gradients along seven continuous factor scores. Identified sensory subgroups were further differentiated by the severity of core and co-occurring symptoms, and level of adaptive functioning, providing novel evidence on the associated clinical correlates of sensory subgroups. These sensory subgroups provide a platform to further interrogate the neurobiological and genetic correlates of altered sensory processing in ASD.

Project description:Multiple lines of evidence indicate a strong genetic contribution to autism spectrum disorders (ASDs). Current guidelines for clinical genetic testing recommend a G-banded karyotype to detect chromosomal abnormalities and fragile X DNA testing, but guidelines for chromosomal microarray analysis have not been established.A cohort of 933 patients received clinical genetic testing for a diagnosis of ASD between January 2006 and December 2008. Clinical genetic testing included G-banded karyotype, fragile X testing, and chromosomal microarray (CMA) to test for submicroscopic genomic deletions and duplications. Diagnostic yield of clinically significant genetic changes was compared.Karyotype yielded abnormal results in 19 of 852 patients (2.23% [95% confidence interval (CI): 1.73%-2.73%]), fragile X testing was abnormal in 4 of 861 (0.46% [95% CI: 0.36%-0.56%]), and CMA identified deletions or duplications in 154 of 848 patients (18.2% [95% CI: 14.76%-21.64%]). CMA results for 59 of 848 patients (7.0% [95% CI: 5.5%-8.5%]) were considered abnormal, which includes variants associated with known genomic disorders or variants of possible significance. CMA results were normal in 10 of 852 patients (1.2%) with abnormal karyotype due to balanced rearrangements or unidentified marker chromosome. CMA with whole-genome coverage and CMA with targeted genomic regions detected clinically relevant copy-number changes in 7.3% (51 of 697) and 5.3% (8 of 151) of patients, respectively, both higher than karyotype. With the exception of recurrent deletion and duplication of chromosome 16p11.2 and 15q13.2q13.3, most copy-number changes were unique or identified in only a small subset of patients.CMA had the highest detection rate among clinically available genetic tests for patients with ASD. Interpretation of microarray data is complicated by the presence of both novel and recurrent copy-number variants of unknown significance. Despite these limitations, CMA should be considered as part of the initial diagnostic evaluation of patients with ASD.

Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males. Gene expression profiling of 116 LCL from autistic (87) and nonautistic (29) individuals were obtained using a custom-printed DNA microarray containing 39,936 elements (TIGR 40K Human array, GPL3427) and a reference design in which each sample was compared to the Stratagene Universal Human RNA standard. The 87 autistic samples were divided into phenotypic subgroups (language, mild, savant) on the basis of cluster analyses of scores from an autism diagnostic questionnaire, the Autism Diagnostic Interview-Revised instrument. Differentially expressed genes were determined for all autistic vs. control groups, as well as for each of 3 phenotypic ASD groups and controls.

Dataset Information

Dissecting the clinical heterogeneity of autism spectrum disorders through defined genotypes.

Publications

Dissecting the clinical heterogeneity of autism spectrum disorders through defined genotypes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets