Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

Satterstrom, F. Kyle; Kosmicki, Jack A.; Wang, Jiebiao; Breen, Michael S.; Rubeis, Silvia De; An, Joon-Yong; Peng, Minshi; Collins, Ryan L.; Grove, Jakob; Klei, Lambertus; Stevens, Christine; Reichert, Jennifer; Mulhern, Maureen; Artomov, Mykyta; Gerges, Sherif; Sheppard, Brooke; Xu, Xiaowei; Bhaduri, Aparna; Norman, Utku; Brand, Harrison; Schwartz, Grace B.; Nguyen, Rachel; Guerrero, Elizabeth E.; Dias, Caroline; Aleksić, Branko; Barbosa, Mafalda; Bishop, Somer; Brusco, Alfredo; Bybjerg‐Grauholm, Jonas; Carracedo, Ángel; Chan, Marcus C.Y.; Chiocchetti, Andreas G.; Chung, Brian Hon Yin; Coon, Hilary; Cuccaro, Michael L.; Currò, Aurora; Bernardina, Bernardo Dalla; Doan, Ryan; Domenici, Enrico; Dong, Shan; Fallerini, Chiara; Fernández-Prieto, Montserrat; Ferrero, Giovanni Battista; Freitag, Christine M.; Fromer, Menachem; Gargus, J. Jay; Giorgio, Elisa; González-Peñas, Javier; Guter, Stephen J.; Halpern, Danielle; Hansen-Kiss, Emily; He, Xin; Herman, Gail E.; Hertz‐Picciotto, Irva; Hougaard, David M.; Hultman, Christina M.; Ionita‐Laza, Iuliana; Jacob, Suma; Jamison, Jesslyn; Jugessur, Astanand; Kaartinen, Miia; Knudsen, Gun Peggy; Kolevzon, Alexander; Kushima, Itaru; Lee, So Lun; Lehtimäki, Terho; Lim, Elaine T.; Lintas, Carla; Lipkin, W. Ian; Lopergolo, Diego; Lopes, Fátima; Ludeña, Yunin; Maciel, Patrı́cia; Magnus, Per; Mahjani, Behrang; Maltman, Nell; Manoach, Dara S.; Meiri, Gal; Menashe, Idan; Miller, Judith S.; Minshew, Nancy J.; Souza, Eduarda Montenegro M. de; Moreira, Danielle de Paula; Morrow, Eric M.; Mors, Ole; Mortensen, Preben Bo; Mosconi, Matthew W.; Muglia, Pierandrea; Neale, Benjamin M.; Nordentoft, Merete; Ozaki, Norio; Palotie, Aarno; Parellada, Mara; Passos‐Bueno, Maria Rita; Pericak‐Vance, Margaret A.; Persico, Antonio M.; Pessah, Isaac N.; Puura, Kaija; Reichenberg, Abraham; Renieri, Alessandra; Riber, Evelise; Robinson, Elise; Samocha, Kaitlin E.; Sandin, Sven; Santangelo, Susan L.; Schellenberg, G D; Scherer, Stephen W.; Schlitt, Sabine; Schmidt, Rebecca J.; Schmitt, Lauren; Silva, Isabela Maya W.; Singh, Tarjinder; Siper, Paige M.; Smith, Moyra; Soares, Gabriela; Stoltenberg, Camilla; Surén, Pål; Süsser, Ezra; Sweeney, John A.; Szatmári, Péter; Tassone, Flora; Teufel, Karoline; Trabetti, Elisabetta; Trelles, Maria del Pilar; Walsh, Christopher A.; Tang, Lara; Weiss, Lauren A.; Werge, Thomas; Werling, Donna M.; Wigdor, Emilie M.; Wilkinson, Emma; Willsey, A. Jeremy; Yu, Timothy W.; Yu, Mullin H.C.; Yuen, Ryan K.C.; Zachi, Elaine Cristina; Betancur, Catalina; Cook, Edwin H.; Gallagher, Louise; Gill, Michael; Sutcliffe, James S.; Thurm, Audrey; Zwick, Michael E.; Børglum, Anders; State, Matthew W.; Çiçek, A. Ercüment; Talkowski, Michael E.; Cutler, David J.; Devlin, Bernie; Sanders, Stephan J.; Roeder, Kathryn; Daly, Mark J.; Buxbaum, Joseph D.

doi:10.2139/ssrn.3371405

Cited by 33 publications

(67 citation statements)

References 19 publications

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“…Both representations describe the same resulting genotype. The other three papers report just one of the contiguous SNVs each [Krupp et al, ]: C‐ > A; [Ji et al, ]; and [Satterstrom et al, ]: C‐>G). This complex variant can also be viewed directly in VariCarta at varicarta.msl.ubc.ca/variant?chr=5&start=134059281&stop=134059281.…”

Section: Resultsmentioning

confidence: 99%

VariCarta: A Comprehensive Database of Harmonized Genomic Variants Found in Autism Spectrum Disorder Sequencing Studies

et al. 2019

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Recent years have seen a boom in the application of the next‐generation sequencing technology to the study of human disorders, including Autism Spectrum Disorder (ASD), where the focus has been on identifying rare, possibly causative genomic variants in ASD individuals. Because of the high genetic heterogeneity of ASD, a large number of subjects is needed to establish evidence for a variant or gene ASD‐association, thus aggregating data across cohorts and studies is necessary. However, methodological inconsistencies and subject overlap across studies complicate data aggregation. Here we present VariCarta, a web‐based database developed to address these challenges by collecting, reconciling, and consistently cataloging literature‐derived genomic variants found in ASD subjects using ongoing semi‐manual curation. The careful manual curation combined with a robust data import pipeline rectifies errors, converts variants into a standardized format, identifies and harmonizes cohort overlaps, and documents data provenance. The harmonization aspect is especially important since it prevents the potential double counting of variants, which can lead to inflation of gene‐based evidence for ASD‐association. The database currently contains 170,416 variant events from 10,893 subjects, collected across 61 publications, and reconciles 16,202 variants that have been reported in literature multiple times. VariCarta is freely accessible at http://varicarta.msl.ubc.ca. Autism Res 2019, 12: 1728–1736. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary The search for genetic factors underlying Autism Spectrum Disorder (ASD) yielded numerous studies reporting potentially causative genomic variants found in ASD individuals. However, methodological differences and subject overlap across studies complicate the assembly of these data, diminishing its utility and accessibility. We developed VariCarta, a web‐based database that aggregates carefully curated, annotated, and harmonized literature‐derived variants identified in individuals with ASD using ongoing semi‐manual curation.

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Section: Resultsmentioning

confidence: 99%

VariCarta: A Comprehensive Database of Harmonized Genomic Variants Found in Autism Spectrum Disorder Sequencing Studies

et al. 2019

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“…The DenovolyzerByClass function paired with the includeGenes option in the DenovolyzeR program was used to test if more DNMs were observed than expected in a particular set of genes. Again, 95% confidence interval were displayed for the enrichment values, as in the autism study by Satterstrom et al 19 . Because prevalence differs between males and females, the rate of observed DNMs is expected to differ between males and females for any mutation exerting the same effect on both sexes on the liability scale.…”

Section: Statistical Analysis Of De Novo Variantsmentioning

confidence: 99%

Codingde novomutations identified by WGS reveal novel orofacial cleft genes

Bishop

Perez

Sun

et al. 2020

Preprint

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While de novo mutations (DNMs) are known to increase risk of congenital defects, DNMs have not been fully explored regarding orofacial clefts (OFCs), one of the most common human birth defects. Therefore, whole-genome sequencing of 756 case-parent trios of European, Colombian, and Taiwanese ancestry was performed to determine the contributions of coding DNMs to OFC risk. Overall, we identified a significant excess of loss-of-function DNMs in genes highly expressed in craniofacial tissues, as well as genes associated with known autosomal dominant OFC syndromes. This analysis also revealed roles for zinc-finger homeobox domain and SOX2-interacting genes in OFC etiology.

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“…Finally, we interrogated transcriptional programs for enrichment (relative to all WT+KO ) in variants conferring risk for different disorders. Early-transient -/-, -stable -/and -increasing -/sets had an increased rate of de novo LoF mutations contributing to NDD and ASD (Satterstrom et al, 2019) (Figure 6E). Comparing the magnitude of the increase, a clear gradient was evident from NDD to ASD to SZ ( Figure 6F).…”

Section: Risk Variants For Other Neuropsychiatric Disorders Display Dmentioning

confidence: 99%

DLG2 knockout reveals neurogenic transcriptional programs underlying neuropsychiatric disorders and cognition

Sanders

D’Andrea

Collins³

et al. 2020

Preprint

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Genetic studies robustly implicate perturbation of DLG2-scaffolded mature postsynaptic signalling complexes in schizophrenia. Here we study in vitro cortical differentiation of DLG2 -/human embryonic stem cells via integrated phenotypic, gene expression and disease genetic analyses. This uncovers a developmental role for DLG2 in the regulation of neural stem cell proliferation and adhesion, and the activation of transcriptional programs during early excitatory corticoneurogenesis. Down-regulation of these programs in DLG2 -/lines delays expression of cell-type identity and causes marked deficits in neuronal migration, morphology and active properties. Genetic risk factors for neuropsychiatric and neurodevelopmental disorders converge on these neurogenic programs, each disorder displaying a distinct pattern of enrichment. These data unveil an intimate link between neurodevelopmental and mature signalling deficits contributing to disease -suggesting a dual role for known synaptic risk genes -and reveal a common pathophysiological framework for studying the neurodevelopmental origins of Mendelian and genetically complex mental disorders. Results Knockout generation and validationTwo DLG2 -/lines were created from H7 hESCs using the CRISPR/Cas9-D10A nickase system targeting the first PDZ domain ( Figure S1). Sequencing revealed no off-target mutations (see Methods, Figure S2 & Table S1). A significant decrease in DLG2 mRNA was observed for exons spanning the first PDZ domain, with a similar decrease inferred for PDZ-containing transcripts, indicating degradation of DLG2 -/transcripts via nonsense-mediated decay ( Figure S3A, B). Quantitative mass spectrometry-based proteomic analysis of peptide-affinity pulldowns using the NMDA receptor NR2 subunit PDZ peptide ligand (Husi and Grant, 2001) confirmed the presence of DLG2 in pulldowns from WT but not DLG2 -/lines ( Figure S3C-F & Table S2). Genotyping revealed no CNVs in either DLG2 -/line relative to WT ( Figure S4A). Both DLG2 -/lines expressed pluripotency markers OCT4, SOX2 and NANOG at 100% of WT levels ( Figure S4B-E). Cells were extensively characterised for their cortical identity using western blotting and immunocytochemistry from day 20 to 60 ( Figure S5). Over 90% of day 20 cells were positive for FOXG1, PAX6 and SOX2 confirming their dorsal forebrain fate ( Figure S5A-B). DLG2 regulates neural stem-cell proliferation and adhesionRNA was extracted in triplicate from each line at 4 timepoints spanning cortical excitatory neuron development (Figure 1A, B) and gene expression quantified. To robustly identify genes dysregulated by DLG2 knockout, expression data from the 2 DLG2 -/lines were pooled and compared to a WT sister line at each timepoint (see Methods). Disruption of DLG2 had a profound effect: of the >13,000 protein-coding genes expressed at each timepoint, ~7% were differentially expressed between DLG2 -/and WT at day 15, rising to 40-60% between days 20 and 30 then decreasing to ~25% by day 60 ( Figure 1C). Strikingly, the 3 genes with the strongest ...

show abstract

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

Cited by 33 publications

References 19 publications

VariCarta: A Comprehensive Database of Harmonized Genomic Variants Found in Autism Spectrum Disorder Sequencing Studies

VariCarta: A Comprehensive Database of Harmonized Genomic Variants Found in Autism Spectrum Disorder Sequencing Studies

Codingde novomutations identified by WGS reveal novel orofacial cleft genes

DLG2 knockout reveals neurogenic transcriptional programs underlying neuropsychiatric disorders and cognition

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