ArticleOrphanet journal of rare diseases2022
Rare disorders have many faces: in silico characterization of rare disorder spectrum.
Article in Orphanet journal of rare diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 27 citations in OpenAlex.
- Trial
- A Multimodal Biomedical Transformer Fusion Network for Disease-Level Rare-Disease-Inheritance Classification Using Ontology-Enriched Text, Metadata, and Gene Associations.Biomedicines · 2026Article
- Uncovering the Molecular Signatures of Rare Genetic Diseases in the Punjabi Population.International journal of molecular sciences · 2025Observational
- CFTR corrector C17 rescues defective SERCA1 in bovine pseudomyotonia: a potential therapy for Brody myopathy.Human molecular genetics · 2025Article
- Advancing the frontier of rare disease modeling: a critical appraisal of in silico technologies.NPJ digital medicine · 2025Review
- Insights on Clinical Development of Cell and Gene Therapy for Rare Diseases-by DahShu Innovative Design Scientific Working Group (IDSWG).Therapeutic innovation & regulatory science · 2025Review
- Untargeted proteomics enables ultra-rapid variant prioritisation in mitochondrial and other rare diseases.Genome medicine · 2025Article
- 2024 VCP International Conference: Exploring multi-disciplinary approaches from basic science of valosin containing protein, an AAA+ ATPase protein, to the therapeutic advancement for VCP-associated multisystem proteinopathy.Neurobiology of disease · 2025Review
- Prevalence of Individuals With Multiple Diagnosed Genetic Diseases in the Undiagnosed Diseases Network.American journal of medical genetics. Part A · 2025Article
- Genetic basis of osteogenesis imperfecta from a single tertiary centre in South Africa.European journal of human genetics : EJHG · 2024Article
- Diet and Nutrients in Rare Neurological Disorders: Biological, Biochemical, and Pathophysiological Evidence.Nutrients · 2024Review
- FiTMuSiC: leveraging structural and (co)evolutionary data for protein fitness prediction.Human genomics · 2024Article
- GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM.BMC bioinformatics · 2024Article
- Recent developments in gene therapy research in India.Journal of biosciences · 2024Review
- A deep learning transformer model predicts high rates of undiagnosed rare disease in large electronic health systems.medRxiv : the preprint server for health sciences · 2023Article
- The Power of Clinical Diagnosis for Deciphering Complex Genetic Mechanisms in Rare Diseases.Genes · 2023Review
- Rule of Prevention: a potential framework to evaluate preventive interventions for rare diseases.Journal of market access & health policy · 2023Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe diagnostic journey for many rare disease patients remains challenging despite use of latest genetic technological advancements. We hypothesize that some patients remain undiagnosed due to more complex diagnostic scenarios that are currently not considered in genome analysis pipelines. To better understand this, we characterized the rare disorder (RD) spectrum using various bioinformatics resources (e.g., Orphanet/Orphadata, Human Phenotype Ontology, Reactome pathways) combined with custom-made R scripts.
resultsOur in silico characterization led to identification of 145 borderline-common, 412 rare and 2967 ultra-rare disorders. Based on these findings and point prevalence, we would expect that approximately 6.53%, 0.34%, and 0.30% of individuals in a randomly selected population have a borderline-common, rare, and ultra-rare disorder, respectively (equaling to 1 RD patient in 14 people). Importantly, our analyses revealed that (1) a higher proportion of borderline-common disorders were caused by multiple gene defects and/or other factors compared with the rare and ultra-rare disorders, (2) the phenotypic expressivity was more variable for the borderline-common disorders than for the rarer disorders, and (3) unique clinical characteristics were observed across the disorder categories forming the spectrum.
conclusionsRecognizing that RD patients who remain unsolved even after genome sequencing might belong to the more common end of the RD spectrum support the usage of computational pipelines that account for more complex genetic and phenotypic scenarios.
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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 OpenQuestion graph.