Using Whole-Exome Sequencing to Identify Inherited Causes of Autism

Yu, Timothy W.; Chahrour, Maria H.; Coulter, Michael; Jiralerspong, Sarn; Okamura‐Ikeda, Kazuko; Ataman, Bulent; Schmitz-Abe, Klaus; Harmin, David A.; Adli, Mazhar; Malik, Athar N.; D’Gama, Alissa M.; Lim, Elaine T.; Sanders, Stephan; Mochida, Ganeshwaran H.; Partlow, Jennifer N.; Sunu, Christine; Felie, Jillian M.; Rodriguez, Jacqueline; Nasir, Ramzi; Ware, Janice; Joseph, Robert M.; Hill, Robert S.; Kwan, Benjamin Y. M.; Al‐Saffar, Muna; Mukaddes, Nahit Motavallı; Hashmi, Asif; Balkhy, Soher; Gascon, Generoso G.; Hisama, Fuki M.; LeClair, Elaine; Poduri, Annapurna; Öner, Özgür; Al-Saad, Samira; Al-Awadi, S A; Bastaki, Lailá; Ben‐Omran, Tawfeg; Teebi, Ahmad S.; Al‐Gazali, Lihadh; Eapen, Valsamma; Stevens, Christine; Rappaport, Leonard; Gabriel, Stacey; Markianos, Kyriacos; State, Matthew W.; Greenberg, Michael E.; Taniguchi, Hiroyuki; Braverman, Nancy; Morrow, Eric M.; Walsh, Christopher A.

doi:10.1016/j.neuron.2012.11.002

Cited by 407 publications

(366 citation statements)

References 74 publications

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“…The 3 high-morbidity subgroups had distinct pathophysiologies; the heterogeneity of the ASD comorbidity spectrum mirrors the heterogeneity observed in genome-wide studies of variants associated with ASD [65][66][67] and gene expression. 68 How our pathophysiological subgroups map to genome-scale heterogeneity remains unknown, but our subgroups suggest a group structure worth investigating with these molecular measures.…”

Section: Figurementioning

confidence: 74%

Comorbidity Clusters in Autism Spectrum Disorders: An Electronic Health Record Time-Series Analysis

2014

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WHAT'S KNOWN ON THIS SUBJECT: Individuals with autism spectrum disorders have a higher comorbidity burden than the general pediatric population, including higher rates of seizures, psychiatric illness, and gastrointestinal disorders. WHAT THIS STUDY ADDS:Comorbidities do not occur evenly. Our clustering analysis reveals subgroups characterized by seizure, psychiatric disorders, and complex multisystem disorders including auditory and gastrointestinal disorders. Correlations between seizure, psychiatric disorders, and gastrointestinal disorders are validated on a sample from a second hospital. abstract OBJECTIVE: The distinct trajectories of patients with autism spectrum disorders (ASDs) have not been extensively studied, particularly regarding clinical manifestations beyond the neurobehavioral criteria from the Diagnostic and Statistical Manual of Mental Disorders. The objective of this study was to investigate the patterns of cooccurrence of medical comorbidities in ASDs.METHODS: International Classification of Diseases, Ninth Revision codes from patients aged at least 15 years and a diagnosis of ASD were obtained from electronic medical records. These codes were aggregated by using phenotype-wide association studies categories and processed into 1350-dimensional vectors describing the counts of the most common categories in 6-month blocks between the ages of 0 to 15. Hierarchical clustering was used to identify subgroups with distinct courses.RESULTS: Four subgroups were identified. The first was characterized by seizures (n = 120, subgroup prevalence 77.5%). The second (n = 197) was characterized by multisystem disorders including gastrointestinal disorders (prevalence 24.3%) and auditory disorders and infections (prevalence 87.8%), and the third was characterized by psychiatric disorders (n = 212, prevalence 33.0%). The last group (n = 4316) could not be further resolved. The prevalence of psychiatric disorders was uncorrelated with seizure activity (P = .17), but a significant correlation existed between gastrointestinal disorders and seizures (P , .001). The correlation results were replicated by using a second sample of 496 individuals from a different geographic region.CONCLUSIONS: Three distinct patterns of medical trajectories were identified by unsupervised clustering of electronic health record diagnoses. These may point to distinct etiologies with different genetic and environmental contributions. Additional clinical and molecular characterizations will be required to further delineate these subgroups.

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Section: Figurementioning

confidence: 74%

Comorbidity Clusters in Autism Spectrum Disorders: An Electronic Health Record Time-Series Analysis

2014

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“…102 However, recent data using exome and whole genome sequencing methods suggest the yield of such testing for clinically informative variants may be much higher. 103,104 Moreover, although the contribution of specific biomarkers to risk prediction may be modest, combined results from a panel of predisposing biomarkers can produce information about an individual' s probability of developing ASD. 105 Consideration of several biomarkers at once is consistent with the multitude of genetic and epigenetic factors (and potentially other biological factors [eg, immune, indices of atypical brain growth/connectivity]) that likely play a role in vulnerability to ASD in many children.…”

Section: Examine the Effectiveness Of Repeat Screeningmentioning

confidence: 99%

Early Screening of Autism Spectrum Disorder: Recommendations for Practice and Research

et al. 2015

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This article reviews current evidence for autism spectrum disorder (ASD) screening based on peer-reviewed articles published to December 2013. Screening provides a standardized process to ensure that children are systematically monitored for early signs of ASD to promote earlier diagnosis. The current review indicates that screening in children aged 18 to 24 months can assist in early detection, consistent with current American Academy of Pediatrics' recommendations. We identify ASD-specific and broadband screening tools that have been ev-aluated in large community samples which show particular promise in terms of accurate classification and clinical utility. We also suggest strategies to help overcome challenges to implementing ASD screening in community practice, as well as priorities for future research. Pediatrics 2015;136:S41-S59

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“…This project identified an enrichment of implicated loci with genes that were regulated by neuronal activity [6]. These studies also identified a number of mutations in these pedigrees, for example the endosomal Na + /H + exchanger 9 (NHE9), glycine metabolic genes, and SYNE1 [6,181]. Some of the genes implicated showed comparable mutations in autism pedigrees without recent shared ancestry.…”

Section: Recessive Loci In Asdmentioning

confidence: 93%

“…Some of the genes implicated showed comparable mutations in autism pedigrees without recent shared ancestry. In addition, some pathways showed evidence supportive of transheterozygous mutations, that is, heterozygous mutations in 2 genes in a common pathway [181]. This genetic mechanism is commonly encountered in model organisms [182]; however, this mechanism of inheritance has not been exhaustively studied.…”

Section: Recessive Loci In Asdmentioning

confidence: 99%

Discovery of Rare Mutations in Autism: Elucidating Neurodevelopmental Mechanisms

et al. 2015

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Autism spectrum disorder (ASD) is a group of highly genetic neurodevelopmental disorders characterized by language, social, cognitive, and behavioral abnormalities. ASD is a complex disorder with a heterogeneous etiology. The genetic architecture of autism is such that a variety of different rare mutations have been discovered, including rare monogenic conditions that involve autistic symptoms. Also, de novo copy number variants and single nucleotide variants contribute to disease susceptibility. Finally, autosomal recessive loci are contributing to our understanding of inherited factors. We will review the progress that the field has made in the discovery of these rare genetic variants in autism. We argue that mutation discovery of this sort offers an important opportunity to identify neurodevelopmental mechanisms in disease. The hope is that these mechanisms will show some degree of convergence that may be amenable to treatment intervention.

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Using Whole-Exome Sequencing to Identify Inherited Causes of Autism

Cited by 407 publications

References 74 publications

Comorbidity Clusters in Autism Spectrum Disorders: An Electronic Health Record Time-Series Analysis

Comorbidity Clusters in Autism Spectrum Disorders: An Electronic Health Record Time-Series Analysis

Early Screening of Autism Spectrum Disorder: Recommendations for Practice and Research

Discovery of Rare Mutations in Autism: Elucidating Neurodevelopmental Mechanisms

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