A dysmorphic feature is an abnormal difference in body structure. It can be an isolated finding in an otherwise normal individual, or it can be related to a congenital disorder, geneticsyndrome or birth defect. Dysmorphology is the study of dysmorphic features, their origins and proper nomenclature. One of the key challenges in identifying and describing dysmorphic features is the use and understanding of specific terms between different individuals.[1]Clinical geneticists and pediatricians are usually those most closely involved with the identification and description of dysmorphic features, as most are apparent during childhood.
Dysmorphic features can vary from isolated, mild anomalies such as clinodactyly or synophrys to severe congenital anomalies, such as heart defects and holoprosencephaly. In some cases, dysmorphic features are part of a larger clinical picture, sometimes known as a sequence, syndrome or association.[2] Recognizing the patterns of dysmorphic features is an important part of a geneticist's diagnostic process, as many genetic disease present with a common collection of features.[1] There are several commercially available databases that allow clinicians to input their observed features in a patient to generate a differential diagnosis.[1][3] These databases are not infallible, as they require on the clinician to provide their own experience, particularly when the observed clinical features are general. A male child with short stature and hypertelorism could have several different disorders, as these findings are not highly specific.[1] However a finding such as 2,3-toe syndactyly raises the index of suspicion for Smith–Lemli–Opitz syndrome.[4]
Most open source projects that perform phenotype-driven disease or gene prioritization work with the terminology of the Human Phenotype Ontology. This controlled vocabulary can be used to describe the clinical features of a patient and is suitable for machine learning approaches. Publicly accessible databases that labs use to deposit their diagnostic findings, such as ClinVar, can be used to build knowledge graphs to explore the clinical feature space.[5]
Dysmorphic features are invariably present from birth, although some are not immediately apparent upon visual inspection. They can be divided into groups based on their origin, including malformations (abnormal development), disruptions (damage to previously normal tissue), deformations (damage caused by an outside physical force) and dysplasias (abnormal growth or organization within a tissue).[1][2]
Dysmorphologyedit
Dysmorphology is the discipline of using dysmorphic features in the diagnostic workup and delineation of syndromic disorders. In the recent years advances in computer vision have also resulted in several deep learning approaches that assist geneticists in the study of the facial gestalt.[6][7][8] Training and test data for clinicians and computer scientists in order to compare the performance of new AIs can be obtained from GestaltMatcher.[citation needed]
Referencesedit
^ abcdeReardon, W.; Donnai, D. (2007). "Dysmorphology demystified". Archives of Disease in Childhood: Fetal and Neonatal Edition. 92 (3): F225–F229. doi:10.1136/adc.2006.110619. PMC2675338. PMID 17449858.
^ abMaitra, Anirban; Kumar, Vinay (2004). "Diseases of Infancy and Childhood". In Kumar, Vinay; Abbas, Abul L.; Fausto, Nelson (eds.). Robbins and Coltran Pathologic Basis of Disease (7th ed.). Philadelphia: Elsevier. pp. 469–508. ISBN978-0-7216-0187-8.
^Fryns, J.-P.; De Ravel, T. D. (2002). "London Dysmorphology Database, London Neurogenetics Database and Dysmorphology Photo Library on CD-ROM \Version 3] 2001". Human Genetics. 111 (1): 113. doi:10.1007/s00439-002-0759-6. PMID 12136245. S2CID 20083700.
^Nowaczyk, M. J.; Waye, J. S. (2001). "The Smith-Lemli-Opitz syndrome: A novel metabolic way of understanding developmental biology, embryogenesis, and dysmorphology". Clinical Genetics. 59 (6): 375–386. doi:10.1034/j.1399-0004.2001.590601.x. PMID 11453964. S2CID 9146017.
^Ferry, Quentin; Steinberg, Julia; Webber, Caleb; FitzPatrick, David R; Ponting, Chris P; Zisserman, Andrew; Nellåker, Christoffer (2014-06-24). Tollman, Stephen (ed.). "Diagnostically relevant facial gestalt information from ordinary photos". eLife. 3: e02020. doi:10.7554/eLife.02020. ISSN 2050-084X. PMC4067075. PMID 24963138.
^Gurovich, Yaron; Hanani, Yair; Bar, Omri; Nadav, Guy; Fleischer, Nicole; Gelbman, Dekel; Basel-Salmon, Lina; Krawitz, Peter M.; Kamphausen, Susanne B.; Zenker, Martin; Bird, Lynne M. (January 2019). "Identifying facial phenotypes of genetic disorders using deep learning". Nature Medicine. 25 (1): 60–64. doi:10.1038/s41591-018-0279-0. ISSN 1546-170X. PMID 30617323. S2CID 57574514.
^Hsieh, Tzung-Chien; Bar-Haim, Aviram; Moosa, Shahida; Ehmke, Nadja; Gripp, Karen W.; Pantel, Jean Tori; Danyel, Magdalena; Mensah, Martin Atta; Horn, Denise; Fleischer, Nicole; Bonini, Guilherme (2021-01-04). "GestaltMatcher: Overcoming the limits of rare disease matching using facial phenotypic descriptors". medRxiv10.1101/2020.12.28.20248193v1.
April 14, 2024
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A dysmorphic feature is an abnormal difference in body structure It can be an isolated finding in an otherwise normal individual or it can be related to a congenital disorder genetic syndrome or birth defect Dysmorphology is the study of dysmorphic features their origins and proper nomenclature One of the key challenges in identifying and describing dysmorphic features is the use and understanding of specific terms between different individuals 1 Clinical geneticists and pediatricians are usually those most closely involved with the identification and description of dysmorphic features as most are apparent during childhood Multiple dysmorphic features in a patient with Pitt Rogers Danks syndrome microcephalia micrognathia and protrusion of the eyeballsDysmorphic features can vary from isolated mild anomalies such as clinodactyly or synophrys to severe congenital anomalies such as heart defects and holoprosencephaly In some cases dysmorphic features are part of a larger clinical picture sometimes known as a sequence syndrome or association 2 Recognizing the patterns of dysmorphic features is an important part of a geneticist s diagnostic process as many genetic disease present with a common collection of features 1 There are several commercially available databases that allow clinicians to input their observed features in a patient to generate a differential diagnosis 1 3 These databases are not infallible as they require on the clinician to provide their own experience particularly when the observed clinical features are general A male child with short stature and hypertelorism could have several different disorders as these findings are not highly specific 1 However a finding such as 2 3 toe syndactyly raises the index of suspicion for Smith Lemli Opitz syndrome 4 Most open source projects that perform phenotype driven disease or gene prioritization work with the terminology of the Human Phenotype Ontology This controlled vocabulary can be used to describe the clinical features of a patient and is suitable for machine learning approaches Publicly accessible databases that labs use to deposit their diagnostic findings such as ClinVar can be used to build knowledge graphs to explore the clinical feature space 5 Dysmorphic features are invariably present from birth although some are not immediately apparent upon visual inspection They can be divided into groups based on their origin including malformations abnormal development disruptions damage to previously normal tissue deformations damage caused by an outside physical force and dysplasias abnormal growth or organization within a tissue 1 2 Dysmorphology editDysmorphology is the discipline of using dysmorphic features in the diagnostic workup and delineation of syndromic disorders In the recent years advances in computer vision have also resulted in several deep learning approaches that assist geneticists in the study of the facial gestalt 6 7 8 Training and test data for clinicians and computer scientists in order to compare the performance of new AIs can be obtained from GestaltMatcher citation needed References edit a b c d e Reardon W Donnai D 2007 Dysmorphology demystified Archives of Disease in Childhood Fetal and Neonatal Edition 92 3 F225 F229 doi 10 1136 adc 2006 110619 PMC 2675338 PMID 17449858 a b Maitra Anirban Kumar Vinay 2004 Diseases of Infancy and Childhood In Kumar Vinay Abbas Abul L Fausto Nelson eds Robbins and Coltran Pathologic Basis of Disease 7th ed Philadelphia Elsevier pp 469 508 ISBN 978 0 7216 0187 8 Fryns J P De Ravel T D 2002 London Dysmorphology Database London Neurogenetics Database and Dysmorphology Photo Library on CD ROM Version 3 2001 Human Genetics 111 1 113 doi 10 1007 s00439 002 0759 6 PMID 12136245 S2CID 20083700 Nowaczyk M J Waye J S 2001 The Smith Lemli Opitz syndrome A novel metabolic way of understanding developmental biology embryogenesis and dysmorphology Clinical Genetics 59 6 375 386 doi 10 1034 j 1399 0004 2001 590601 x PMID 11453964 S2CID 9146017 Peng Chengyao Dieck Simon Schmid Alexander Ahmad Ashar Knaus Alexej Wenzel Maren Mehnert Laura Zirn Birgit Haack Tobias Ossowski Stephan Wagner Matias Brunet Teresa Ehmke Nadja Danyel Magdalena Rosnev Stanislav Kamphans Tom Nadav Guy Fleischer Nicole Frohlich Holger Krawitz Peter 2021 CADA Phenotype driven gene prioritization based on a case enriched knowledge graph pp lqab078 medRxiv 10 1101 2021 03 01 21251705 Ferry Quentin Steinberg Julia Webber Caleb FitzPatrick David R Ponting Chris P Zisserman Andrew Nellaker Christoffer 2014 06 24 Tollman Stephen ed Diagnostically relevant facial gestalt information from ordinary photos eLife 3 e02020 doi 10 7554 eLife 02020 ISSN 2050 084X PMC 4067075 PMID 24963138 Gurovich Yaron Hanani Yair Bar Omri Nadav Guy Fleischer Nicole Gelbman Dekel Basel Salmon Lina Krawitz Peter M Kamphausen Susanne B Zenker Martin Bird Lynne M January 2019 Identifying facial phenotypes of genetic disorders using deep learning Nature Medicine 25 1 60 64 doi 10 1038 s41591 018 0279 0 ISSN 1546 170X PMID 30617323 S2CID 57574514 Hsieh Tzung Chien Bar Haim Aviram Moosa Shahida Ehmke Nadja Gripp Karen W Pantel Jean Tori Danyel Magdalena Mensah Martin Atta Horn Denise Fleischer Nicole Bonini Guilherme 2021 01 04 GestaltMatcher Overcoming the limits of rare disease matching using facial phenotypic descriptors medRxiv 10 1101 2020 12 28 20248193v1 Retrieved from https en wikipedia org w index php title Dysmorphic feature amp oldid 1191141965, wikipedia, wiki, book, books, library,
