The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.
The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry. The Catalog contains variant-trait associations and supporting metadata for >45 000 published GWAS across >5000 human traits, and >40 000 full P-value summary statistics datasets. Content is curated from publications or acquired via author submission of prepublication summary statistics through a new submission portal and validation tool. GWAS data volume has vastly increased in recent years. We have updated our software to meet this scaling challenge and to enable rapid release of submitted summary statistics. The scope of the repository has expanded to include additional data types of high interest to the community, including sequencing-based GWAS, gene-based analyses and copy number variation analyses. Community outreach has increased the number of shared datasets from under-represented traits, e.g. cancer, and we continue to contribute to awareness of the lack of population diversity in GWAS. Interoperability of the Catalog has been enhanced through links to other resources including the Polygenic Score Catalog and the International Mouse Phenotyping Consortium, refinements to GWAS trait annotation, and the development of a standard format for GWAS data.
De novo disruptions of the neural transcription factor FOXP1 are a recently discovered, rare cause of sporadic intellectual disability (ID). We report three new cases of FOXP1-related disorder identified through clinical whole-exome sequencing. Detailed phenotypic assessment confirmed that global developmental delay, autistic features, speech/language deficits, hypotonia and mild dysmorphic features are core features of the disorder. We expand the phenotypic spectrum to include sensory integration disorder and hypertelorism. Notably, the etiological variants in these cases include two missense variants within the DNA-binding domain of FOXP1. Only one such variant has been reported previously. The third patient carries a stop-gain variant. We performed functional characterization of the three missense variants alongside our stop-gain and two previously described truncating/frameshift variants. All variants severely disrupted multiple aspects of protein function. Strikingly, the missense variants had similarly severe effects on protein function as the truncating/frameshift variants. Our findings indicate that a loss of transcriptional repression activity of FOXP1 underlies the neurodevelopmental phenotype in FOXP1-related disorder. Interestingly, the three novel variants retained the ability to interact with wild-type FOXP1, suggesting these variants could exert a dominant-negative effect by interfering with the normal FOXP1 protein. These variants also retained the ability to interact with FOXP2, a paralogous transcription factor disrupted in rare cases of speech and language disorder. Thus, speech/language deficits in these individuals might be worsened through deleterious effects on FOXP2 function. Our findings highlight that de novo FOXP1 variants are a cause of sporadic ID and emphasize the importance of this transcription factor in neurodevelopment.
Fetal akinesia refers to a broad spectrum of disorders in which the unifying feature is a reduction or lack of fetal movement. Fetal akinesias may be caused by defects at any point along the motor system pathway including the central and peripheral nervous system, the neuromuscular junction and the muscle, as well as by restrictive dermopathy or external restriction of the fetus in utero. The fetal akinesias are clinically and genetically heterogeneous, with causative mutations identified to date in a large number of genes encoding disparate parts of the motor system. However, for most patients, the molecular cause remains unidentified. One reason for this is because the tools are only now becoming available to efficiently and affordably identify mutations in a large panel of disease genes. Next-generation sequencing offers the promise, if sufficient cohorts of patients can be assembled, to identify the majority of the remaining genes on a research basis and facilitate efficient clinical molecular diagnosis. The benefits of identifying the causative mutation(s) for each individual patient or family include accurate genetic counselling and the options of prenatal diagnosis or preimplantation genetic diagnosis. In this review, we summarise known single-gene disorders affecting the spinal cord, peripheral nerves, neuromuscular junction or skeletal muscles that result in fetal akinesia. This audit of these known molecular and pathophysiological mechanisms involved in fetal akinesia provides a basis for improved molecular diagnosis and completing disease gene discovery.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.