A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex

Antaki, Danny; Maihofer, Adam X.; Klein, Marieke; Guevara, James P.; Grove, Jakob; Carey, Caitlin E.; Hong, Oanh; Arranz, Maria; Hervás, Amaia; Corsello, Christina; Muotria, A.; Iakoucheva, Lilia M.; Courchesne, Eric; Pierce, Karen; Gleeson, Joseph G.; Robinson, Elise; Nievergelt, Caroline M.; Sebat, Jonathan

doi:10.1101/2021.03.30.21254657

Cited by 23 publications

(42 citation statements)

References 57 publications

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“…The copyright holder for this preprint this version posted September 1, 2021. ; https://doi.org/10.1101/2021.08.30.21262845 doi: medRxiv preprint most severely affected autistic females in our cohort carry more rare variants that impact their severity, as recent analyses by [68] suggest. These two explanations are, of course, not mutually exclusive.…”

Section: /20mentioning

confidence: 58%

Clinical autism subscales have common genetic liabilities that are heritable, pleiotropic, and generalizable to the general population

Thomas

Koomar

Casten

et al. 2021

Preprint

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The complexity of autism's phenotypic spectra is well-known, yet most genetic research uses case-control status as the target trait. It is unclear whether clinical autism instruments such as the Social Communication Questionnaire (SCQ), Repetitive Behaviors Scale-Revised (RBS-R), and Developmental Coordination Disorder Questionnaire (DCDQ) are more genetically informative than case-control. We employed the SPARK autism cohort (N = 6,449) to illuminate the genetic etiology of these twelve subscales. In comparison to the heritability of autism case-control at 0.12, the RBS-R subscales were increased, ranging from 0.18 to 0.30 (all p < 0.05). Heritability of the DCDQ subscales ranged from 0.07 to 0.09 and the SCQ subscales from 0 to 0.09 (all p > 0.05). We also found evidence for genetic correlations among the RBS-R, SCQ, and DCDQ. GWAS followed by projection of polygenic scores (PGS) into ABCD revealed significant associations with CBCL social and thought problems, while the autism case-control PGS did not significantly associate. In phenotypic correlation analyses, the autism case-control PGS did not predict the subscales in SPARK, and sex-stratified correlations showed no effect in males and a surprising negative effect in females. Notably, other PGS did predict the subscales, with the strongest being educational attainment negatively correlated, while ADHD and major depression were positively correlated. Overall, our analyses suggest that clinical subscales are more genetically powerful than case-control, and that of the three instruments investigated, the RBS-R shows the greatest evidence of common genetic signal in both autistic and general population samples.

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Section: /20mentioning

confidence: 58%

Clinical autism subscales have common genetic liabilities that are heritable, pleiotropic, and generalizable to the general population

Thomas

Koomar

Casten

et al. 2021

Preprint

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“…In line with previous results, 17,20,21 the number of high-impact de novo variants (protein truncating single nucleotide variants and structural variants, and missense variants with MPC score > 2, N = 2,863 to 4,442) was associated with reduced measures of IQ, adaptive behaviour, and motor coordination. Despite the expanded sample size 17,20,21 and more fine-grained phenotypes 19 investigated compared to previous analyses, these variants were not robustly associated with any of the core autism features (Figure 2B, Supplementary Table 9). The effect sizes of the PGS did not attenuate after controlling for the presence of high impact de novo variants (Figure 2C, Supplementary Table 9, and Supplementary Figure 6), suggesting largely independent effects between common and rare variants.…”

Section: Common Genetic Variants Are Robustly Associated With Core Autism Features But High-impact De Novo Variants Are Notmentioning

confidence: 70%

“…Previous studies have conducted genotypephenotype association studies of core autism features using summed scores of several autistic trait measures and their subscales in relatively modest sample sizes. [19][20][21] However, these summed scores may capture multiple aggregated latent traits, introducing statistical noise and limiting interpretability of the results. To this end, we combined two widely used parentreport measures of autistic traits -Repetitive Behaviour Scale -Revised (RBS) 28 and Social Communication Questionnaire -Lifetime version (SCQ) 29 -in 24,420 autistic individuals from the Simons Simplex Collection (SSC) 30 and the SPARK 31 cohorts.…”

Section: Identifying Latent Phenotypes In Core Autism Featuresmentioning

confidence: 99%

“…Previous smaller scale studies have identified associations with some autism features and both common and de novo variants. [19][20][21] Here, we expanded both the sample size by combining genetic data from autistic individuals in four cohorts (N max = 12,893), and the number of phenotypes investigated (19 different core and associated features) and conducted genetic association analyses to understand the impact of different classes of genetic variants on these phenotypic features. These 19 features include measures and subscales of measures commonly included for a research diagnosis of autism, parent reports of autistic features, and measures of IQ, adaptive behaviour, and motor coordination (Methods).…”

Section: Common Genetic Variants Are Robustly Associated With Core Autism Features But High-impact De Novo Variants Are Notmentioning

confidence: 99%

“…Whilst a few studies have attempted to investigate the genetic influences on this heterogeneity [11][12][13][14][15][16][17][18] , substantial gaps remain. First, existing studies investigating genotype-phenotype associations have been limited to summed scores of core autism features in smaller sample sizes [19][20][21] rather than the underlying latent dimensions. This distinction is important given that autism is phenotypically dissociable 12,22,23 and some associations may emerge only when latent traits are considered.…”

Section: Introductionmentioning

confidence: 99%

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Genetic correlates of phenotypic heterogeneity in autism

Warrier

Leblond

Cliquet

et al. 2020

Preprint

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Importance Schizophrenia, educational attainment, and intelligence are all genetically correlated with autism. However, autism is a complex condition, with several different core (such as social communication difficulties and repetitive and restricted behaviour) and associated features (such as IQ and adaptive behaviour) contributing to the underlying heterogeneity. It is unknown to what extent polygenic scores (PGS) for these three phenotypes are associated with the core and associated autism features. Objective To investigate the association of PGS for intelligence, educational attainment and schizophrenia on core autism features, IQ and adaptive behaviour in autistic individuals. To further investigate the effects of stratifying by sex and IQ on these associations. Design PGS association for the three phenotypes with 12 different autism core and associated features in three cohorts followed by meta-analysis. We additionally conducted sensitivity analyses by stratifying for sex and IQ. Settings Three cross-sectional, multi-centre cohorts comprising autistic with genotype data, and phenotypic information. Participants Autistic individuals (total N: 2,512 to 3,681) from three different cohorts: Simons Simplex Collection (Nmax = 2,233), Autism Genetic Research Exchange (Nmax = 1,200), and AIMS-2-TRIALS LEAP (Nmax = 262) Main outcome measures Association of PGS for intelligence, educational attainment, and schizophrenia with core autism features, measures of intelligence, and adaptive behaviour in autistic individuals Results We identified a similar pattern of correlation among core and associated autism features across all three cohorts. Cluster analyses of these features identified two broad clusters: one consisting of the core features, and another consisting of IQ and adaptive behaviour. PGS for intelligence were only associated with measures of intelligence and adaptive behaviour (e.g. for full-scale IQ, Beta = 0.08, 95%CI = 0.11 to 0.04) for PGS for educational attainment were associated for measures of intelligence, adaptive behaviour, and additionally, non-verbal communication as measured by ADI which is a core-autism feature (e.g. for full-scale IQ, Beta = 0.05, 95% CI = 0.08 to 0.02; for ADI non-verbal communication, Beta = 0.05, 95% CI = 0.09 tp 0.01). Finally, PGS for schizophrenia were associated with two core autism features: restricted and repetitive behaviour and verbal communication difficulties as measured by the ADI-R (e.g. for ADI restricted and repetitive behaviour: Beta = 0.06, 95% CI = 0.09 to 0.02). Most of these associations were also significant when restricting it to males only or to individuals with IQ > 70. We find limited evidence for heterogeneity between cohorts. Conclusion and relevance We identify specific and different patterns of association between PGS for the three phenotypes and core and associated autism features. This provides greater resolution into the shared genetics between autism and the three phenotypes, and suggests one method to investigate heterogeneity in autism and co-occurring conditions.

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PARK2 microdeletion in a multiplex family with autism spectrum disorder

Barone

Cirnigliaro

Saccuzzo

et al. 2022

Intl J of Devlp Neuroscience

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Background PARK2 (PRKN; MIM*602544) encodes Parkin protein, an ubiquitin‐protein ligase required for proteasomal degradation and operating in the synaptic compartments. Copy number variations (CNVs) involving PARK2 have been associated with autism spectrum disorder (ASD). We report on a family with ASD (multiplex family) harbouring a microdeletion at chr. 6q26 causing PARK2 disruption. Methods CNV analyses were performed using CGH/SNP‐array platforms, and the detected microdeletion was confirmed by real‐time quantitative PCR. Standardized psychometric evaluation was used for neurobehavioral characterization. Results We found an intragenic ~157 kb microdeletion of the chromosomal region 6q26 causing PARK2 disruption in two male sibs with ASD and syndromic phenotype. They both had dysmorphic facial features with coarse faces, deeply set eyes with long horizontal palpebral fissures, long eyelashes and thick eyebrows, fleshy lips and mild skeletal problems. We found an intrafamilial clinical heterogeneity owing to different severity of the autism symptoms between the affected sibs: the younger one had minimally verbal autism and severe intellectual disability, whereas his older brother presented high‐functioning autism and preserved speech. Parental analysis and real‐time PCR using a PRKN fragment mapping within the deletion demonstrated that the deletion was inherited from their father having subthreshold features of ASD consisting with broad autism phenotype. Conclusions The study corroborates the hypothesis that PARK2 aberrations may be associated with ASD and highlights correlations between CNV affecting PARK2 and ASD in a multiplex family. We show remarkable intrafamilial variability in the severity of inherited ASD associated with PARK2 microdeletion.

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A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex

Cited by 23 publications

References 57 publications

Clinical autism subscales have common genetic liabilities that are heritable, pleiotropic, and generalizable to the general population

Clinical autism subscales have common genetic liabilities that are heritable, pleiotropic, and generalizable to the general population

Genetic correlates of phenotypic heterogeneity in autism

PARK2 microdeletion in a multiplex family with autism spectrum disorder

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