ArticleOrphanet journal of rare diseases2021
Model organisms contribute to diagnosis and discovery in the undiagnosed diseases network: current state and a future vision.
Article in Orphanet journal of rare diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02450851 (Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network), which is not on this map. Cited by 59 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network
Who cites it
59 citing papers in PubMed, 83 citations in OpenAlex.
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- Genetic analysis of the X-linked adrenoleukodystrophy gene ABCD1 in Drosophila uncovers a conserved phenotype.Communications biology · 2026Article
- Subtle cellular phenotypes inform pathological and benign genetic mutants in the Iduronate-2 sulfatase gene.Human molecular genetics · 2026Article
- Interpreting the functional impact of genetic variants: The need for context qualifiers.American journal of human genetics · 2026Review
- CrisprBuildr: an open-source application for CRISPR-mediated genome engineering in Drosophila melanogaster.G3 (Bethesda, Md.) · 2026Article
- Gerobiotics: Exploring the Potential and Limitations of Repurposing Probiotics in Addressing Aging Hallmarks and Chronic Diseases.Probiotics and antimicrobial proteins · 2026Review
- Mapping the bioinformatics resource landscape: an analysis of LibGuides across Canadian universities.The journal of the Canadian Health Libraries Association · 2025Article
- A Coffin-Siris syndrome-associated mutation modeled in Caenorhabditis elegans affects multiple developmental processes.G3 (Bethesda, Md.) · 2025Article
- Ribonucleases in Mendelian disease: Characterization and insight from model organisms.Genes & diseases · 2025Review
- Functional assays inGenome research · 2025Review
- Genome-wide prediction of dominant and recessive neurodevelopmental disorder-associated genes.American journal of human genetics · 2025Article
- Optimizing gRNA selection for high-penetrance F0 CRISPR screening for interrogating disease gene function.Nucleic acids research · 2025Article
- The hybrid history of zebrafish.G3 (Bethesda, Md.) · 2025Article
- Prevalence of Individuals With Multiple Diagnosed Genetic Diseases in the Undiagnosed Diseases Network.American journal of medical genetics. Part A · 2025Article
- Zebrafish (International journal of molecular sciences · 2024Review
- Loss-of-function in RBBP5 results in a syndromic neurodevelopmental disorder associated with microcephaly.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
- The ALS-associated KIF5A P986L variant is not pathogenic for Drosophila motoneurons.Scientific reports · 2024Article
- Computational strategies for cross-species knowledge transfer and translational biomedicine.ArXiv · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 1 country.
Funding
Abstract
Decreased sequencing costs have led to an explosion of genetic and genomic data. These data have revealed thousands of candidate human disease variants. Establishing which variants cause phenotypes and diseases, however, has remained challenging. Significant progress has been made, including advances by the National Institutes of Health (NIH)-funded Undiagnosed Diseases Network (UDN). However, 6000-13,000 additional disease genes remain to be identified. The continued discovery of rare diseases and their genetic underpinnings provides benefits to affected patients, of whom there are more than 400 million worldwide, and also advances understanding the mechanisms of more common diseases. Platforms employing model organisms enable discovery of novel gene-disease relationships, help establish variant pathogenicity, and often lead to the exploration of underlying mechanisms of pathophysiology that suggest new therapies. The Model Organism Screening Center (MOSC) of the UDN is a unique resource dedicated to utilizing informatics and functional studies in model organisms, including worm (Caenorhabditis elegans), fly (Drosophila melanogaster), and zebrafish (Danio rerio), to aid in diagnosis. The MOSC has directly contributed to the diagnosis of challenging cases, including multiple patients with complex, multi-organ phenotypes. In addition, the MOSC provides a framework for how basic scientists and clinicians can collaborate to drive diagnoses. Customized experimental plans take into account patient presentations, specific genes and variant(s), and appropriateness of each model organism for analysis. The MOSC also generates bioinformatic and experimental tools and reagents for the wider scientific community. Two elements of the MOSC that have been instrumental in its success are (1) multidisciplinary teams with expertise in variant bioinformatics and in human and model organism genetics, and (2) mechanisms for ongoing communication with clinical teams. Here we provide a position statement regarding the central role of model organisms for continued discovery of disease genes, and we advocate for the continuation and expansion of MOSC-type research entities as a Model Organisms Network (MON) to be funded through grant applications submitted to the NIH, family groups focused on specific rare diseases, other philanthropic organizations, industry partnerships, and other sources of support.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.