Knowledge (XXG)

Dysmorphic feature

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or association. 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. There are several commercially available databases that allow clinicians to input their observed features in
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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
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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; Fröhlich,
58:. 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. 90:
a patient to generate a differential diagnosis. 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
113:. 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 155:
approaches that assist geneticists in the study of the facial gestalt. Training and test data for clinicians and computer scientists in order to compare the performance of new AIs can be obtained from
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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).
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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
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Ferry, Quentin; Steinberg, Julia; Webber, Caleb; FitzPatrick, David R; Ponting, Chris P; Zisserman, Andrew; NellĂĄker, Christoffer (2014-06-24). Tollman, Stephen (ed.).
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Nowaczyk, M. J.; Waye, J. S. (2001). "The Smith-Lemli-Opitz syndrome: A novel metabolic way of understanding developmental biology, embryogenesis, and dysmorphology".
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Fryns, J.-P.; De Ravel, T. D. (2002). "London Dysmorphology Database, London Neurogenetics Database and Dysmorphology Photo Library on CD-ROM \Version 3] 2001".
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are usually those most closely involved with the identification and description of dysmorphic features, as most are apparent during childhood.
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Holger; Krawitz, Peter (2021). "CADA: Phenotype-driven gene prioritization based on a case-enriched knowledge graph". pp. lqab078.
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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
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Maitra, Anirban; Kumar, Vinay (2004). "Diseases of Infancy and Childhood". In Kumar, Vinay; Abbas, Abul L.; Fausto, Nelson (eds.).
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Most open source projects that perform phenotype-driven disease or gene prioritization work with the terminology of the
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could have several different disorders, as these findings are not highly specific. However a finding such as 2,3-toe
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Dysmorphic features are invariably present from birth, although some are not immediately apparent upon
486: 350: 512: 59: 44: 466: 330: 287: 81:. In some cases, dysmorphic features are part of a larger clinical picture, sometimes known as a 491: 458: 450: 411: 393: 355: 322: 279: 242: 216: 125: 78: 442: 401: 383: 314: 271: 206: 198: 19: 118: 406: 371: 211: 186: 156: 318: 506: 152: 148: 95: 91: 28: 470: 430: 291: 334: 129: 70: 63: 55: 32: 446: 275: 99: 454: 397: 202: 137: 133: 74: 462: 415: 326: 283: 220: 132:(abnormal development), disruptions (damage to previously normal tissue), 372:"Diagnostically relevant facial gestalt information from ordinary photos" 86: 82: 51: 48: 431:"Identifying facial phenotypes of genetic disorders using deep learning" 388: 114: 128:. They can be divided into groups based on their origin, including 69:
Dysmorphic features can vary from isolated, mild anomalies such as
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Archives of Disease in Childhood: Fetal and Neonatal Edition
241:(7th ed.). Philadelphia: Elsevier. pp. 469–508. 77:
to severe congenital anomalies, such as heart defects and
140:(abnormal growth or organization within a tissue). 136:(damage caused by an outside physical force) and 239:Robbins and Coltran Pathologic Basis of Disease 23:Multiple dysmorphic features in a patient with 8: 490: 405: 387: 354: 232: 230: 210: 168: 121:to explore the clinical feature space. 16:Abnormal difference in body structure 7: 180: 178: 176: 174: 172: 102:raises the index of suspicion for 14: 319:10.1034/j.1399-0004.2001.590601.x 185:Reardon, W.; Donnai, D. (2007). 35:and protrusion of the eyeballs 1: 492:10.1101/2020.12.28.20248193v1 356:10.1101/2021.03.01.21251705 187:"Dysmorphology demystified" 534: 104:Smith–Lemli–Opitz syndrome 25:Pitt–Rogers–Danks syndrome 447:10.1038/s41591-018-0279-0 276:10.1007/s00439-002-0759-6 111:Human Phenotype Ontology 203:10.1136/adc.2006.110619 117:, can be used to build 36: 22: 60:Clinical geneticists 389:10.7554/eLife.02020 45:congenital disorder 41:dysmorphic feature 37: 307:Clinical Genetics 248:978-0-7216-0187-8 126:visual inspection 79:holoprosencephaly 525: 518:Medical genetics 497: 496: 494: 481: 475: 474: 426: 420: 419: 409: 391: 367: 361: 360: 358: 345: 339: 338: 302: 296: 295: 259: 253: 252: 234: 225: 224: 214: 197:(3): F225–F229. 182: 119:knowledge graphs 533: 532: 528: 527: 526: 524: 523: 522: 503: 502: 501: 500: 483: 482: 478: 435:Nature Medicine 428: 427: 423: 369: 368: 364: 347: 346: 342: 304: 303: 299: 261: 260: 256: 249: 236: 235: 228: 184: 183: 170: 165: 146: 17: 12: 11: 5: 531: 529: 521: 520: 515: 505: 504: 499: 498: 485:descriptors". 476: 421: 362: 340: 313:(6): 375–386. 297: 264:Human Genetics 254: 247: 226: 167: 166: 164: 161: 157:GestaltMatcher 145: 142: 15: 13: 10: 9: 6: 4: 3: 2: 530: 519: 516: 514: 511: 510: 508: 493: 488: 480: 477: 472: 468: 464: 460: 456: 452: 448: 444: 440: 436: 432: 425: 422: 417: 413: 408: 403: 399: 395: 390: 385: 381: 377: 373: 366: 363: 357: 352: 344: 341: 336: 332: 328: 324: 320: 316: 312: 308: 301: 298: 293: 289: 285: 281: 277: 273: 269: 265: 258: 255: 250: 244: 240: 233: 231: 227: 222: 218: 213: 208: 204: 200: 196: 192: 188: 181: 179: 177: 175: 173: 169: 162: 160: 158: 154: 153:deep learning 150: 149:Dysmorphology 144:Dysmorphology 143: 141: 139: 135: 131: 130:malformations 127: 122: 120: 116: 112: 107: 105: 101: 97: 96:hypertelorism 93: 92:short stature 88: 84: 80: 76: 72: 67: 65: 64:pediatricians 61: 57: 53: 50: 46: 42: 34: 30: 29:microcephalia 26: 21: 479: 441:(1): 60–64. 438: 434: 424: 379: 375: 365: 343: 310: 306: 300: 267: 263: 257: 238: 194: 190: 147: 134:deformations 123: 108: 71:clinodactyly 68: 56:birth defect 40: 38: 33:micrognathia 513:Body shape 507:Categories 382:: e02020. 270:(1): 113. 163:References 138:dysplasias 100:syndactyly 455:1546-170X 398:2050-084X 75:synophrys 471:57574514 463:30617323 416:24963138 327:11453964 292:20083700 284:12136245 221:17449858 87:syndrome 83:sequence 52:syndrome 487:medRxiv 407:4067075 351:medRxiv 335:9146017 212:2675338 115:ClinVar 49:genetic 489:  469:  461:  453:  414:  404:  396:  353:  333:  325:  290:  282:  245:  219:  209:  467:S2CID 376:eLife 331:S2CID 288:S2CID 459:PMID 451:ISSN 412:PMID 394:ISSN 323:PMID 280:PMID 243:ISBN 217:PMID 94:and 62:and 443:doi 402:PMC 384:doi 315:doi 272:doi 268:111 207:PMC 199:doi 73:or 54:or 509:: 465:. 457:. 449:. 439:25 437:. 433:. 410:. 400:. 392:. 378:. 374:. 329:. 321:. 311:59 309:. 286:. 278:. 266:. 229:^ 215:. 205:. 195:92 193:. 189:. 171:^ 159:. 106:. 85:, 47:, 39:A 31:, 27:: 495:. 473:. 445:: 418:. 386:: 380:3 359:. 337:. 317:: 294:. 274:: 251:. 223:. 201::

Index


Pitt–Rogers–Danks syndrome
microcephalia
micrognathia
congenital disorder
genetic
syndrome
birth defect
Clinical geneticists
pediatricians
clinodactyly
synophrys
holoprosencephaly
sequence
syndrome
short stature
hypertelorism
syndactyly
Smith–Lemli–Opitz syndrome
Human Phenotype Ontology
ClinVar
knowledge graphs
visual inspection
malformations
deformations
dysplasias
Dysmorphology
deep learning
GestaltMatcher

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