Online Mendelian Inheritance in Man

Online Mendelian Inheritance in Man
Name	Online Mendelian Inheritance in Man
Established	1966
Country	United States
Language	English
Discipline	Genetics

Contents

Online Mendelian Inheritance in Man

Online Mendelian Inheritance in Man is a comprehensive, authoritative catalog of human genes and genetic phenotypes created to support clinical genetics, biomedical research, and education. It is widely used alongside databases and resources maintained by institutions such as National Institutes of Health, National Library of Medicine, Harvard Medical School, Massachusetts General Hospital, and Rockefeller University. Clinicians, researchers, and educators often pair it with other resources like ClinVar, GeneCards, OMIM-derived tools, PubMed, and GenBank for variant interpretation and literature retrieval.

Overview

OMIM provides detailed entries describing allelic variants, phenotypic descriptions, inheritance patterns, and bibliographic links; its content complements repositories such as Ensembl, UCSC Genome Browser, 1000 Genomes Project, dbSNP, and Human Genome Project. The resource is organized by gene-centric and phenotype-centric entries that connect to primary literature indexed in PubMed Central, to locus data from HUGO Gene Nomenclature Committee, and to clinical catalogs like Orphanet, GeneReviews, and databases created at Broad Institute. OMIM entries are used in conjunction with clinical guidelines from organizations including American College of Medical Genetics and Genomics, World Health Organization, Food and Drug Administration, European Medicines Agency, and National Comprehensive Cancer Network.

OMIM traces its origins to print compilations of genetic disease descriptions developed by clinicians and geneticists influenced by work at Johns Hopkins University, Columbia University, University of Pennsylvania, Yale School of Medicine, and Washington University in St. Louis. The transition from print to an online format involved collaborations among curators associated with National Institutes of Health, editors trained at Harvard Medical School, and contributors linked to research at Cold Spring Harbor Laboratory, Salk Institute, and Max Planck Institute. Major milestones include its early editions which paralleled efforts of the Human Genome Project, the integration of electronic indexing compatible with PubMed searches, and utility in projects such as the Human Variome Project and consortia led by International HapMap Project and 1000 Genomes Project investigators.

Entries in OMIM are structured with standardized headings that reference gene loci, phenotype descriptions, inheritance modes, and curated bibliographies that often cite authors from institutions like Stanford University, University of Cambridge, University of Oxford, Imperial College London, and Karolinska Institutet. Cross-links connect entries to sequence databases maintained by GenBank, nomenclature assigned by HUGO Gene Nomenclature Committee, and variant records in ClinVar and dbVar; users frequently integrate OMIM data with tools developed at European Bioinformatics Institute, Wellcome Sanger Institute, Broad Institute, Bioinformatics Institute Singapore, and European Molecular Biology Laboratory. The catalog uses structured identifiers that enable interoperability with electronic health record systems implemented at Mayo Clinic, Cleveland Clinic, Johns Hopkins Hospital, Mount Sinai Health System, and Kaiser Permanente.

OMIM is hosted and curated with oversight from entities including National Library of Medicine, and its editorial process involves clinical geneticists and molecular biologists affiliated with Johns Hopkins University, Harvard Medical School, Yale School of Medicine, University of California, San Francisco, and University of Chicago. Access policies and licensing discussions have intersected with standards set by organizations such as Creative Commons, Open Data Institute, World Wide Web Consortium, National Institutes of Health, and legal frameworks influenced by rulings in jurisdictions associated with United States Copyright Office and regulatory guidance from U.S. Department of Health and Human Services. Curation pipelines leverage submissions and literature curated from journals associated with publishers like Nature Publishing Group, Elsevier, Wiley-Blackwell, Springer Nature, and American Medical Association.

OMIM has influenced gene discovery, variant interpretation, and rare disease diagnosis in research programs at Broad Institute, Wellcome Sanger Institute, Massachusetts General Hospital, Johns Hopkins University, and Stanford University School of Medicine. Its entries are cited in guidelines from American College of Medical Genetics and Genomics, in clinical decision support systems deployed at Mayo Clinic, and in translational programs at National Cancer Institute, European Society of Human Genetics, Centers for Disease Control and Prevention, and National Health Service (England). Large-scale initiatives such as the All of Us Research Program, UK Biobank, Undiagnosed Diseases Network, and collaborative projects led by Gates Foundation and Chan Zuckerberg Initiative use OMIM-linked annotations for phenotype-driven variant prioritization and study design.

Critiques of OMIM address challenges similar to those raised about curated resources from Nature Genetics, Science Translational Medicine, JAMA, The Lancet, and other publishers: concerns include lag time for newly published variants, scope differences with population databases like gnomAD, potential biases related to literature coverage from centers such as Harvard Medical School and Stanford University, and the need for integration with clinical variant repositories such as ClinVar and DECIPHER. Discussions about open access, licensing, and data sharing reference debates involving Creative Commons, Open Data Institute, and policy frameworks from National Institutes of Health and European Commission. Users and commentators from institutions like Johns Hopkins University, Mayo Clinic, Broad Institute, Wellcome Trust, and European Bioinformatics Institute continue to propose enhancements for interoperability, automated curation, and expanded representation of underreported populations.