Intellectual disability (ID) disorders are genetically and phenotypically extremely heterogeneous. Can this complexity be depicted in a comprehensive way as a means of facilitating the understanding of ID disorders and their underlying biology? We provide a curated database of 746 currently known genes, mutations in which cause ID (ID-associated genes [ID-AGs]), classified according to ID manifestation and associated clinical features. Using this integrated resource, we show that ID-AGs are substantially enriched with co-expression, protein-protein interactions, and specific biological functions. Systematic identification of highly enriched functional themes and phenotypes revealed typical phenotype combinations characterizing process-defined groups of ID disorders, such as chromatin-related disorders and deficiencies in DNA repair. Strikingly, phenotype classification efficiently breaks down ID-AGs into subsets with significantly elevated biological coherence and predictive power. Custom-made functional Drosophila datasets revealed further characteristic phenotypes among ID-AGs and specific clinical classes. Our study and resource provide systematic insights into the molecular and clinical landscape of ID disorders, represent a significant step toward overcoming current limitations in ID research, and prove the utility of systematic human and cross-species phenomics analyses in highly heterogeneous genetic disorders.

BACKGROUND: Although habituation is one of the most ancient and fundamental forms of learning, its regulators and its relevance for human disease are poorly understood. METHODS: We manipulated the orthologs of 286 genes implicated in intellectual disability (ID) with or without comorbid autism spectrum disorder (ASD) specifically in Drosophila neurons, and we tested these models in light-off jump habituation. We dissected neuronal substrates underlying the identified habituation deficits and integrated genotype-phenotype annotations, gene ontologies, and interaction networks to determine the clinical features and molecular processes that are associated with habituation deficits. RESULTS: We identified .100 genes required for habituation learning. For 93 of these genes, a role in habituation learning was previously unknown. These genes characterize ID disorders with macrocephaly and/or overgrowth and comorbid ASD. Moreover, individuals with ASD from the Simons Simplex Collection carrying damaging de novo mutations in these genes exhibit increased aberrant behaviors associated with inappropriate, stereotypic speech. At the molecular level, ID genes required for normal habituation are enriched in synaptic function and converge on Ras/mitogen-activated protein kinase (Ras/MAPK) signaling. Both increased Ras/MAPK signaling in gamma-aminobutyric acidergic (GABAergic) neurons and decreased Ras/MAPK signaling in cholinergic neurons specifically inhibit the adaptive habituation response. CONCLUSIONS: Our work supports the relevance of habituation learning to ASD, identifies an unprecedented number of novel habituation players, supports an emerging role for inhibitory neurons in habituation, and reveals an opposing, circuit-level-based mechanism for Ras/MAPK signaling. These findings establish habituation as a possible, widely applicable functional readout and target for pharmacologic intervention in ID/ASD.

We have developed the Weighted Gene Expression Tool and database (WeGET, http://weget.cmbi.umcn.nl) for the prediction of new genes of a molecular system by correlated gene expression. WeGET utilizes a compendium of 465 human and 560 murine gene expression datasets that have been collected from multiple tissues under a wide range of experimental conditions. It exploits this abundance of expression data by assigning a high weight to datasets in which the known genes of a molecular system are harmoniously up- and down-regulated. WeGET ranks new candidate genes by calculating their weighted co-expression with that system. A weighted rank is calculated for human genes and their mouse orthologs. Then, an integrated gene rank and p-value is computed using a rank-order statistic. We applied our method to predict novel genes that have a high degree of co-expression with Gene Ontology terms and pathways from KEGG and Reactome. For each query set we provide a list of predicted novel genes, computed weights for transcription datasets used and cell and tissue types that contributed to the final predictions. The performance for each query set is assessed by 10-fold cross-validation. Finally, users can use the WeGET to predict novel genes that co-express with a custom query set.

Attention deficit hyperactivity disorder (ADHD) is a highly heritable psychiatric disorder. The objective of this study was to define ADHD-associated candidate genes and their associated molecular modules and biological themes, based on the analysis of rare genetic variants. Methods:The authors combined data from 11 published copy number variation studies in 6,176 individuals with ADHD and 25,026 control subjects and prioritized genes by applying an integrative strategy based on criteria including recurrence in individuals with ADHD, absence in control subjects, complete coverage in copy number gains, and presence in the minimal region common to overlapping copy number variants (CNVs), as well as on protein-protein interactions and information from cross-species genotype-phenotype annotation.Results: The authors localized 2,241 eligible genes in the 1,532 reported CNVs, of which they classified 432 as highpriority ADHD candidate genes. The high-priority ADHD candidate genes were significantly coexpressed in the brain. A network of 66 genes was supported by ADHD-relevant phenotypes in the cross-species database. Four significantly interconnected protein modules were found among the high-priority ADHD genes. A total of 26 genes were observed across all applied bioinformatic methods. Lookup in the latest genome-wide association study for ADHD showed that among those 26 genes, POLR3C and RBFOX1 were also supported by common genetic variants.Conclusions: Integration of a stringent filtering procedure in CNV studies with suitable bioinformatics approaches can identify ADHD candidate genes at increased levels of credibility. The authors' analytic pipeline provides additional insight into the molecular mechanisms underlying ADHD and allows prioritization of genes for functional validation in validated model organisms.

60Background: Although habituation is one of the most ancient and fundamental forms of learning, its 61 regulators and relevance for human disease are poorly understood. 62Methods: We manipulated the orthologs of 286 genes implicated in intellectual disability (ID) with or 63 without comorbid autism spectrum disorder (ASD) specifically in Drosophila neurons, and tested 64 these models in light-off jump habituation. We dissected neuronal substrates underlying the 65 identified habituation deficits and integrated genotype-phenotype annotations, gene ontologies and 66 interaction networks to determine the clinical features and molecular processes that are associated 67 with habituation deficits. 68Results: We identified more than 100 genes required for habituation learning. For the vast majority 69 of these, 93 genes, a role in habituation learning was previously unknown. These genes characterize 70 ID disorders with macrocephaly/overgrowth and comorbid ASD. Moreover, ASD individuals from the 71 Simons Simplex Collection (SSC) carrying damaging de novo mutations in these genes exhibit 72 increased aberrant behaviors associated with inappropriate, stereotypic speech. At the molecular 73 level, ID genes required for normal habituation are enriched in synaptic function and converge on 74Ras-MAPK signaling. Both increased Ras-MAPK signaling in GABAergic and decreased Ras-MAPK 75 signaling in cholinergic neurons specifically inhibit the adaptive habituation response. 76Conclusions: Our work supports the relevance of habituation learning to autism, identifies an 77 unprecedented number of novel habituation players, supports an emerging role for inhibitory 78 neurons in habituation and reveals an opposing, circuit-level-based mechanism for Ras-MAPK 79 signaling. This establishes habituation as a possible, widely applicable functional readout and target 80 for pharmacologic intervention in ID/ASD. 81 82 described in a fraction of ASD individuals (9-11), but has not been connected yet to specific genetic 96 defects, with a single exception. Recently, two independent studies demonstrated habituation 97 deficits in patients with Fragile X syndrome, the most common monogenic cause of intellectual 98 disability (ID) and ASD (12, 13), confirming previously reported habituation deficits in Fmr1 KO mice 99 (14, 15). Habituation deficits have also been reported in a limited number of other ID or ASD 100 (ID/ASD) disease models (16)(17)(18)(19). 101Because assessing human gene function in habituation is challenging, we utilized a cross-102 species approach. We apply light-off jump habituation in Drosophila to increase our knowledge on 103 the genetic control of habituation and, at the same time, to address the relevance of decreased 104 habituation in ID and in comorbid ASD disorders. Since ID is present in 70% of individuals with ASD 105 (20), monogenic causes of ID provide a unique molecular windows to ASD pathology (21). Drosophila 106 is a powerful, well-established model for ID (22)(23)(24) and offers genome-wide resources to st...