bims-tyki2d Biomed News
on Thymidine kinase 2 deficiency
Issue of 2026–07–12
two papers selected by
Zoya Panahloo, UCB
  1. Implementation of exome sequencing for rare undiagnosed diseases in LMICs: the G2MC rare diseases exome sequencing pilot project.
  2. The Orphanet Nomenclature and Classification of Rare Diseases for Improved Patient Recognition and Data Interoperability: Qualitative and Quantitative Analysis.
  1. Hum Genet. 2026 Jul 08. pii: 61. [Epub ahead of print]145(1):
    Implementation of exome sequencing for rare undiagnosed diseases in LMICs: the G2MC rare diseases exome sequencing pilot project.
    Yasas D Kolambage, Claudia Gonzaga-Jauregui, Guillermo Lay-Son, Rupesh Mishra, Njabulo Christian Mabaso, Sok-Kun Tae, Kristin A Maloney, Carolina I Galaz-Montoya, Dineshani Hettiarachchi, Bronwyn Dillon, Nilam Thakur, Ludivine de Menten, Cecilia Mellado, Carol L Greene, Toni I Pollin, Amanda Krause, Meow-Keong Thong, Alan R Shuldiner, Vajira H W Dissanayake.
      Rare undiagnosed diseases impose a substantial burden on patients, families, and health systems. Collectively they affect an estimated 300-350 million people worldwide. Of these, approximately 250 million live in low- and middle-income countries (LMICs). Many rare diseases have a genetic basis and can be diagnosed using molecular testing. However, patients in LMICs often lack access to advanced diagnostics and specialist care, leading to prolonged diagnostic odysseys and significant distress. To address this gap, the Global Genomic Medicine Collaborative (G2MC) implemented a Rare Disease Pilot Project to enable clinical genomic testing at six LMIC sites (Chile, Malaysia, Mexico, Nepal, South Africa, Sri Lanka). Using trio exome sequencing for 18 selected families, supplemented by chromosomal microarray as indicated, definitive molecular diagnoses were established in 5 families (pathogenic/likely pathogenic variants explaining the phenotype). An additional 8 families had suspected molecular diagnoses with strong phenotype correlation that require functional validation, while 5 families remained undiagnosed at the end of the pilot. The integration of genomic data into clinical decision-making enabled definitive diagnoses, precise management, and genetic counseling for these patients. The pilot also strengthened local capacity building by conducting cross-site case conferences and enabling local reanalysis of sequence data at sites with bioinformatics capabilities. This study demonstrates the feasibility, effectiveness, and adaptability of implementing exome sequencing in resource-limited settings and highlights its potential to transform rare disease diagnosis and care in LMICs.
    DOI:  https://doi.org/10.1007/s00439-026-02849-y
  2. JMIR Med Inform. 2026 Jul 08. 14 e84553
    The Orphanet Nomenclature and Classification of Rare Diseases for Improved Patient Recognition and Data Interoperability: Qualitative and Quantitative Analysis.
    Caterina Lucano, David Lagorce, Annie Olry, Houda Ali, Valérie Lanneau, Mickael De Carvalho, Aysegul Dilsizoglu Senol, Marta Fructuoso, Emilie Gaillard, Marie-Cécile Gaillard, Seed Mihic, Mariana Tannoury, Florence Sauvage, Charlotte Rodwell, Sylvie Maiella, Marc Hanauer, Ana Rath.
       BACKGROUND: Although individually uncommon, rare diseases (RDs) collectively affect an estimated 329-624 million people worldwide. There are over 6500 known RDs, 85% of which affect fewer than 1 person per million. Consequently, the critical amount of data necessary to improve knowledge, care, and treatment can only be achieved through cumulative data collection across countries. However, RDs remain underrepresented in medical terminologies and classification systems, hindering data sharing, interoperability, and public health monitoring.
    OBJECTIVE: This paper presents the Orphanet Nomenclature and Classification of RDs detailing its content, production and update methodology, and mappings to other semantic resources. It also provides an up-to-date count of RDs based on the consensus operational definition describing their distribution by medical domain.
    METHODS: The Orphanet Nomenclature of RDs is a multilingual standardized system composed of clinical entities, each defined by a unique and time-stable ORPHAcode, a preferred term, synonyms, a classification level, and a textual definition. This nomenclature is structured into 3 classification levels organized within a multihierarchical and multiparental classification system by medical domain. Its production, updates, and mappings to major biomedical resources rely on standardized and published procedures, continuous literature review, manual curation, and expert validation, reflecting advancements in RDs knowledge and clinical practice. Presented data metrics were computed using the Orphanet July 2025 release to quantitatively characterize the content, structure, classification, and semantic alignments of the Orphanet Nomenclature and Classification system.
    RESULTS: As of July 2025, the Orphanet Nomenclature of RDs includes a total of 9784 active clinical entities, including 6527 disorders (corresponding to the RDs definition), 1084 subtypes of disorders, and 2173 groups of disorders. Disorders are multiclassified into 29 classification hierarchies, each corresponding to a distinct medical domain, accurately representing the complex multisystemic nature of RDs. Extensive qualified mappings ensure semantic interoperability: 97.4% (6355/6527) of disorders are mapped to at least 1 ICD-10 (International Statistical Classification of Diseases, Tenth Revision) code (415/6527, 6.4% with an exact proximity relationship), 71.8% (4683/6527) are mapped to at least 1 ICD-11 (International Classification of Diseases, Eleventh Revision) Mortality and Morbidity Statistics code (958/6527, 14.7% with an exact relationship) and 94.8% (6191/6527) are mapped to Systematized Nomenclature of Medicine Clinical Terms (all with an exact relationship). Genetic disorders represent 72.2% (4715/6527) of all RDs, and 63.4% (4141/6527) are mapped to at least 1 phenotypic Online Mendelian Inheritance in Man number.
    CONCLUSIONS: The Orphanet Nomenclature and Classification of RDs is the only RDs-specific interoperable medical terminology meeting the needs of health care, research, and public health systems. By addressing the underrepresentation of RDs in medical terminologies, it enables accurate RDs identification, coding, and monitoring, supporting cross-border data interoperability, and contributing to improved knowledge, policymaking, and ultimately better care for people living with an RD.
    Keywords:  Interoperability; ORPHAcodes; classification; codification; medical terminology; nomenclature; rare diseases
    DOI:  https://doi.org/10.2196/84553
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