Dataset Information

A Genetics-First Approach to Dissecting the Heterogeneity of Autism: Phenotypic Comparison of Autism Risk Copy Number Variants.

ABSTRACT:

Objective

Certain copy number variants (CNVs) greatly increase the risk of autism. The authors conducted a genetics-first study to investigate whether heterogeneity in the clinical presentation of autism is underpinned by specific genotype-phenotype relationships.

Methods

This international study included 547 individuals (mean age, 12.3 years [SD=4.2], 54% male) who were ascertained on the basis of having a genetic diagnosis of a rare CNV associated with high risk of autism (82 16p11.2 deletion carriers, 50 16p11.2 duplication carriers, 370 22q11.2 deletion carriers, and 45 22q11.2 duplication carriers), as well as 2,027 individuals (mean age, 9.1 years [SD=4.9], 86% male) with autism of heterogeneous etiology. Assessments included the Autism Diagnostic Interview-Revised and IQ testing.

Results

The four genetic variant groups differed in autism symptom severity, autism subdomain profile, and IQ profile. However, substantial variability was observed in phenotypic outcome in individual genetic variant groups (74%-97% of the variance, depending on the trait), whereas variability between groups was low (1%-21%, depending on the trait). CNV carriers who met autism criteria were compared with individuals with heterogeneous autism, and a range of profile differences were identified. When clinical cutoff scores were applied, 54% of individuals with one of the four CNVs who did not meet full autism diagnostic criteria had elevated levels of autistic traits.

Conclusions

Many CNV carriers do not meet full diagnostic criteria for autism but nevertheless meet clinical cutoffs for autistic traits. Although profile differences between variants were observed, there is considerable variability in clinical symptoms in the same variant.

SUBMITTER: Chawner SJRA

PROVIDER: S-EPMC8022239 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Genetics-First Approach to Dissecting the Heterogeneity of Autism: Phenotypic Comparison of Autism Risk Copy Number Variants.

Chawner Samuel J R A SJRA Doherty Joanne L JL Anney Richard J L RJL Antshel Kevin M KM Bearden Carrie E CE Bernier Raphael R Chung Wendy K WK Clements Caitlin C CC Curran Sarah R SR Cuturilo Goran G Fiksinski Ania M AM Gallagher Louise L Goin-Kochel Robin P RP Gur Raquel E RE Hanson Ellen E Jacquemont Sebastien S Kates Wendy R WR Kushan Leila L Maillard Anne M AM McDonald-McGinn Donna M DM Mihaljevic Marina M Miller Judith S JS Moss Hayley H Pejovic-Milovancevic Milica M Schultz Robert T RT Green-Snyder LeeAnne L Vorstman Jacob A JA Wenger Tara L TL Hall Jeremy J Owen Michael J MJ van den Bree Marianne B M MBM

The American journal of psychiatry 20210101 1

<h4>Objective</h4>Certain copy number variants (CNVs) greatly increase the risk of autism. The authors conducted a genetics-first study to investigate whether heterogeneity in the clinical presentation of autism is underpinned by specific genotype-phenotype relationships.<h4>Methods</h4>This international study included 547 individuals (mean age, 12.3 years [SD=4.2], 54% male) who were ascertained on the basis of having a genetic diagnosis of a rare CNV associated with high risk of autism (82 16 ...[more]

PMID: 33384013

Similar Datasets

Project description:BackgroundAutism spectrum disorders and schizophrenia have been associated with an overlapping set of copy number variant loci, but the nature and degree of overlap in copy number variants (deletions compared to duplications) between these two disorders remains unclear.MethodsWe systematically evaluated three lines of evidence: (1) the statistical bases for associations of autism spectrum disorders and schizophrenia with a set of the primary CNVs thus far investigated, from previous studies; (2) data from case series studies on the occurrence of these CNVs in autism spectrum disorders, especially among children, and (3) data on the extent to which the CNVs were associated with intellectual disability and developmental, speech, or language delays. We also conducted new analyses of existing data on these CNVs in autism by pooling data from seven case control studies.ResultsFour of the CNVs considered, dup 1q21.1, dup 15q11-q13, del 16p11.2, and dup 22q11.21, showed clear statistical evidence as autism risk factors, whereas eight CNVs, del 1q21.1, del 3q29, del 15q11.2, del 15q13.3, dup 16p11.2, dup 16p13.1, del 17p12, and del 22q11.21, were strongly statistically supported as risk factors for schizophrenia. Three of the CNVs, dup 1q21.1, dup 16p11.2, and dup 16p13.1, exhibited statistical support as risk factors for both autism and schizophrenia, although for each of these CNVs statistical significance was nominal for tests involving one of the two disorders. For the CNVs that were statistically associated with schizophrenia but were not statistically associated with autism, a notable number of children with the CNVs have been diagnosed with autism or ASD; children with these CNVs also demonstrate a high incidence of intellectual disability and developmental, speech, or language delays.ConclusionsThese findings suggest that although CNV loci notably overlap between autism and schizophrenia, the degree of strongly statistically supported overlap in specific CNVs at these loci remains limited. These analyses also suggest that relatively severe premorbidity to CNV-associated schizophrenia in children may sometimes be diagnosed as autism spectrum disorder.

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.

Dataset Information

A Genetics-First Approach to Dissecting the Heterogeneity of Autism: Phenotypic Comparison of Autism Risk Copy Number Variants.

Objective

Methods

Results

Conclusions

Publications

A Genetics-First Approach to Dissecting the Heterogeneity of Autism: Phenotypic Comparison of Autism Risk Copy Number Variants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets