Dataset Information

Nosology and classification of genetic skeletal disorders: 2010 revision.

ABSTRACT: Genetic disorders involving the skeletal system arise through disturbances in the complex processes of skeletal development, growth and homeostasis and remain a diagnostic challenge because of their variety. The Nosology and Classification of Genetic Skeletal Disorders provides an overview of recognized diagnostic entities and groups them by clinical and radiographic features and molecular pathogenesis. The aim is to provide the Genetics, Pediatrics and Radiology community with a list of recognized genetic skeletal disorders that can be of help in the diagnosis of individual cases, in the delineation of novel disorders, and in building bridges between clinicians and scientists interested in skeletal biology. In the 2010 revision, 456 conditions were included and placed in 40 groups defined by molecular, biochemical, and/or radiographic criteria. Of these conditions, 316 were associated with mutations in one or more of 226 different genes, ranging from common, recurrent mutations to "private" found in single families or individuals. Thus, the Nosology is a hybrid between a list of clinically defined disorders, waiting for molecular clarification, and an annotated database documenting the phenotypic spectrum produced by mutations in a given gene. The Nosology should be useful for the diagnosis of patients with genetic skeletal diseases, particularly in view of the information flood expected with the novel sequencing technologies; in the delineation of clinical entities and novel disorders, by providing an overview of established nosologic entities; and for scientists looking for the clinical correlates of genes, proteins and pathways involved in skeletal biology.

SUBMITTER: Warman ML

PROVIDER: S-EPMC3166781 | biostudies-other | 2011 May

REPOSITORIES: biostudies-other

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Nosology and classification of genetic skeletal disorders: 2010 revision.

Warman Matthew L ML Cormier-Daire Valerie V Hall Christine C Krakow Deborah D Lachman Ralph R LeMerrer Martine M Mortier Geert G Mundlos Stefan S Nishimura Gen G Rimoin David L DL Robertson Stephen S Savarirayan Ravi R Sillence David D Spranger Juergen J Unger Sheila S Zabel Bernhard B Superti-Furga Andrea A

American journal of medical genetics. Part A 20110315 5

Genetic disorders involving the skeletal system arise through disturbances in the complex processes of skeletal development, growth and homeostasis and remain a diagnostic challenge because of their variety. The Nosology and Classification of Genetic Skeletal Disorders provides an overview of recognized diagnostic entities and groups them by clinical and radiographic features and molecular pathogenesis. The aim is to provide the Genetics, Pediatrics and Radiology community with a list of recogni ...[more]

PMID: 21438135

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Project description:The 2019 International Skeletal Dysplasia Society nosology update lists 441 genes for which mutations result in rare human skeletal disorders. These genes code for enzymes (33%), scaffolding proteins (18%), signal transduction proteins (16%), transcription factors (14%), cilia proteins (8%), extracellular matrix proteins (5%), and membrane transporters (4%). Skeletal disorders include aggrecanopathies, channelopathies, ciliopathies, cohesinopathies, laminopathies, linkeropathies, lysosomal storage diseases, protein-folding and RNA splicing defects, and ribosomopathies. With the goal of evaluating the ability of mouse models to mimic these human genetic skeletal disorders, a PubMed literature search identified 260 genes for which mutant mice were examined for skeletal phenotypes. These mouse models included spontaneous and ENU-induced mutants, global and conditional gene knockouts, and transgenic mice with gene over-expression or specific base-pair substitutions. The human X-linked gene ARSE and small nuclear RNA U4ATAC, a component of the minor spliceosome, do not have mouse homologs. Mouse skeletal phenotypes mimicking human skeletal disorders were observed in 249 of the 260 genes (96%) for which comparisons are possible. A supplemental table in spreadsheet format provides PubMed weblinks to representative publications of mutant mouse skeletal phenotypes. Mutations in 11 mouse genes (Ccn6, Cyp2r1, Flna, Galns, Gna13, Lemd3, Manba, Mnx1, Nsd1, Plod1, Smarcal1) do not result in similar skeletal phenotypes observed with mutations of the homologous human genes. These discrepancies can result from failure of mouse models to mimic the exact human gene mutations. There are no obvious commonalities among these 11 genes. Body BMD and/or radiologic dysmorphology phenotypes were successfully identified for 28 genes by the International Mouse Phenotyping Consortium (IMPC). Forward genetics using ENU mouse mutagenesis successfully identified 37 nosology gene phenotypes. Since many human genetic disorders involve hypomorphic, gain-of-function, dominant-negative and intronic mutations, future studies will undoubtedly utilize CRISPR/Cas9 technology to examine transgenic mice having genes modified to exactly mimic variant human sequences. Mutant mice will increasingly be employed for drug development studies designed to treat human genetic skeletal disorders. Significance:Great progress is being made identifying mutant genes responsible for human rare genetic skeletal disorders and mouse models for genes affecting bone mass, architecture, mineralization and strength. This review organizes data for 441 human genetic bone disorders with regard to heredity, gene function, molecular pathways, and fidelity of relevant mouse models to mimic the human skeletal disorders. PubMed weblinks to citations of 249 successful mouse models are provided.

Project description:Inherited platelet disorders (IPDs), which manifest as primary hemostasis defects, often underlie abnormal bleeding and a family history of thrombocytopenia, bone marrow failure, hematologic malignancies, undefined mucocutaneous bleeding disorder, or congenital bony defects. Wide heterogeneity in IPD types with regard to the presence or absence of thrombocytopenia, platelet dysfunction, bone marrow failure, and dysmegakaryopoiesis is observed in patients. The individual processes involved in platelet production and hemostasis are genetically controlled; to date, mutations of more than 50 genes involved in various platelet biogenesis steps have been implicated in IPDs. Representative IPDs resulting from defects in specific pathways, such as thrombopoietin/MPL signaling; transcriptional regulation; granule formation, trafficking, and secretion; proplatelet formation; cytoskeleton regulation; and transmembrane glycoprotein signaling are reviewed, and the underlying gene mutations are discussed based on the National Center for Biotechnology Information database and Online Mendelian Inheritance in Man accession number. Further, the status and prevalence of genetically confirmed IPDs in Korea are explored based on searches of the PubMed and KoreaMed databases. IPDs are congenital bleeding disorders that can be dangerous due to unexpected bleeding and require genetic counseling for family members and descendants. Therefore, the pediatrician should be suspicious and aware of IPDs and perform the appropriate tests if the patient has unexpected bleeding. However, all IPDs are extremely rare; thus, the domestic incidences of IPDs are unclear and their diagnosis is difficult. Diagnostic confirmation or differential diagnoses of IPDs are challenging, time-consuming, and expensive, and patients are frequently misdiagnosed. Comprehensive molecular characterization and classification of these disorders should enable accurate and precise diagnosis and facilitate improved patient management.

Project description:PURPOSE:We previously developed and validated informatic algorithms that used International Classification of Diseases 9th revision (ICD9)-based diagnostic and procedure codes to detect the presence and timing of cancer recurrence (the RECUR Algorithms). In 2015, ICD10 replaced ICD9 as the worldwide coding standard. To understand the impact of this transition, we evaluated the performance of the RECUR Algorithms after incorporating ICD10 codes. METHODS:Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of the algorithms using gold standard recurrence measures associated with a contemporary cohort of patients with stage I to III breast, colorectal, and lung (excluding IIIB) cancer and derived performance measures, including the area under the receiver operating curve, average absolute prediction error, and correct classification rate. These values were compared with the performance measures derived from the validation of the original algorithms. RESULTS:A total of 659 colorectal, 280 lung, and 2,053 breast cancer cases were identified. Area under the receiver operating curve derived from the updated algorithms was 89.0% (95% CI, 82.3% to 95.7%), 88.9% (95% CI, 79.3% to 98.2%), and 80.5% (95% CI, 72.8% to 88.2%) for the colorectal, lung, and breast cancer algorithms, respectively. Average absolute prediction errors for recurrence timing were 2.7 (SE, 11.3%), 2.4 (SE, 10.4%), and 5.6 months (SE, 21.8%), respectively, and timing estimates were within 6 months of actual recurrence for more than 80% of colorectal, more than 90% of lung, and more than 50% of breast cancer cases using the updated algorithm. CONCLUSION:Performance measures derived from the updated and original algorithms had overlapping confidence intervals, suggesting that the ICD9 to ICD10 transition did not affect the RECUR Algorithm performance.

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Nosology and classification of genetic skeletal disorders: 2010 revision.

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Nosology and classification of genetic skeletal disorders: 2010 revision.

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