在人类表型本体论中对癫痫发作进行建模—根据当代ILAE概念使大的表型数据易于处理_Journal of Epilepsy

Authors：

 DavidLewis-Smith , PeterD Galer , GannaBalagura , 黄格格　牛永利　译 , 杨建仲　审

Corresponding author：

DavidLewis-Smith, Email: helbigi@email.chop.edu

Keywords：

大数据; 分类; 癫痫; 遗传学

DOI：

10.7507/2096-0247.202205013

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

癫痫的临床特征决定了如何定义癫痫，进而指导治疗。因此，在对癫痫病因、轨迹和治疗反应的研究中，考虑构成癫痫的基本临床实体至关重要。人类表型本体论（Human phenotype ontology，HPO）广泛应用于临床和遗传学研究中用于临床特征的简明交流和建模，其允许使用逻辑推理来协调提取的数据。我们试图重新设计HPO癫痫亚本体，以提高其与当前癫痫概念的一致性，同时支持在高通量临床和基因组研究中应用大型临床数据集。根据2017年国际抗癫痫联盟对癫痫发作类型的分类，我们创建了一个新的HPO癫痫亚本体，并在不同细节层次上整合了癫痫持续状态、热性惊厥、反射性发作和新生儿癫痫的概念。我们比较了修订前后的HPO癫痫亚本体，根据3个独立队列中791例患者的癫痫发作信息可以推断：其中2个独立队列的信息先前已发表过，还有150例患者是新招募的。每个队列的数据以不同的格式提供，并通过两个版本的HPO进行协调。新的癫痫亚本体将癫痫发作的描述性概念数量增加了5倍。可标注到队列中的癫痫发作描述符号数量增加了40%，关于个体癫痫发作的信息总量增加了38%。最重要的定性差异是局灶性进展为双侧强直-阵挛发作与全面起始和局灶起始发作的关系。我们已经生成了一个详细的当代概念图，用于协调临床癫痫发作数据，并在2020-12-07 HPO的官方版本中实施，并在hpo.jax.org免费提供。这将有助于克服基因组学中的表型瓶颈，促进有价值数据的再利用，并最终提高对癫痫的诊断和精准治疗。

Citation： DavidLewis-Smith, PeterD Galer, GannaBalagura, 黄格格　牛永利　译, 杨建仲　审. 在人类表型本体论中对癫痫发作进行建模—根据当代ILAE概念使大的表型数据易于处理. Journal of Epilepsy, 2022, 8(5): 457-468. doi: 10.7507/2096-0247.202205013 Copy

1.	Helbig I, Riggs ER, Barry CA, et al. The ClinGen Epilepsy Gene Curation Expert Panel—Bridging the divide between clinical domain knowledge and formal gene curation criteria. Hum Mutat, 2018, 39(5): 1476-1484.
2.	Greenberg DA, Subaran R. Blinders, phenotype, and fashionable genetic analysis: a critical examination of the current state of epilepsy genetic studies. Epilepsia, 2011, 52(1): 1-9.
3.	Lhatoo SD, Bernasconi N, Blumcke I, et al. Big data in epilepsy: clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy. Epilepsia, 2020, 61(6): 1869-1883.
4.	Scheffer IE, Berkovic S, Capovilla G, et al. ILAE classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia, 2017, 58(2): 512-521.
5.	Fisher RS, Cross JH, D’Souza C, French JA, Haut SR, Higurashi N, et al. Instruction manual for the ILAE 2017 operational classification of seizure types. Epilepsia, 2017, 58(2): 531-542.
6.	Fisher RS, Cross JH, French JA, et al. Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 2017, 58(2): 522-530.
7.	Fisher RS, Acevedo C, Arzimanoglou A, Bogacz A, Cross JH, Elger CE, et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia, 2014, 55(2): 475-482.
8.	Lüders H, Vaca GFB, Akamatsu N, et al. Classification of paroxysmal events and the four-dimensional epilepsy classification system. Epileptic Disord, 2019, 21(1): 1-29.
9.	Blume WT, Luders HO, Mizrahi E, Tassinari C, Van Emde Boas W, Engel J. Glossary of descriptive terminology for ictal semiology: report of the ILAE Task Force on Classification and Terminology. Epilepsia, 2001, 42(4): 1212-1218.
10.	Commission on Classification and Terminology of the International League Against Epilepsy. Proposal for revised clinical and electro-encephalographic classification of epileptic seizures. Epilepsia, 1981, 22(2): 489-501.
11.	Berg AT, Berkovic SF, Brodie MJ, et al. Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005–2009. Epilepsia, 2010, 51(3): 676-685.
12.	Lüders H, Acharya J, Baumgartner C, et al. Semiological seizure classification. Epilepsia, 1998, 39(4): 1006-1013.
13.	Akawi N, McRae J, Ansari M, et al. Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4, 125 families. Nat Genet, 2015, 47(5): 1363-1369.
14.	Turro E, Astle WJ, Megy K, et al. Whole-genome sequencing of patients with rare diseases in a national health system. Nature, 2020, 583(1): 96-102.
15.	Lindy AS, Stosser MB, Butler E, et al. Diagnostic outcomes for genetic testing of 70 genes in 8565 patients with epilepsy and neurodevelopmental disorders. Epilepsia, 2018, 59(4): 1062-1071.
16.	Truty R, Patil N, Sankar R, et al. Possible precision medicine implications from genetic testing using combined detection of sequence and intragenic copy number variants in a large cohort with childhood epilepsy. Epilepsia Open, 2019, 4(2): 397-408.
17.	International League Against Epilepsy Consortium on Complex Epilepsies. Genome-wide megaanalysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies. Nat Commun, 2018, 9: 5269.
18.	Epi25 Collaborative. Ultra-rare genetic variation in the epilepsies: a whole-exome sequencing study of 17, 606 individuals. Am J Hum Genet, 2019, 105: 267-282.
19.	NHS Health Education England. Requesting whole genome sequencing: information for clinicians. Available at:https://www.genomicseducation.hee.nhs.uk/supporting-the-nhs-genomic medicine-service/requesting-whole-genome-sequencing-information-for-clinicians/.Accessed Dec 2020.
20.	Gruber TR. A translation approach to portable ontology specifications. Knowledge Acquisition, 1993, 5: 199-220.
21.	Kohler S, Gargano M, Matentzoglu N, et al. The human phenotype ontology in 2021. Nucleic Acids Res, 2021, 49: 1207-1217.
22.	McKusick-Nathans Institute of Genetic Medicine JHUB, MD. Online Mendelian Inheritance in Man, OMIM®. Available at:https://omim.org/.Accessed 10 Dec 2020.
23.	SNOMED International. SNOMED Clinical Terms. Available at:https://www.snomed.org/snomedct/sct-worldwide.Accessed 10 Dec 2020.
24.	Helbig I, Lopez-Hernandez T, Shor O, et al. A recurrent missense variant in AP2M1 impairs clathrin-mediated endocytosis and causes developmental and epileptic encephalopathy. Am J Hum Genet, 2019, 104: 1060-1072.
25.	Galer PD, Ganesan S, Lewis-Smith D, et al. Semantic similarity analysis reveals robust gene-disease relationships in developmental and epileptic encephalopathies. Am J Hum Genet, 2020, 107: 683-697.
26.	Ganesan S, Galer PD, Helbig KL, et al. A longitudinal footprint of genetic epilepsies using automated electronic medical record interpretation. Genet Med, 2020, 22: 2060-2070.
27.	Son JH, Xie G, Yuan C, et al. Deep phenotyping on electronic health records facilitates genetic diagnosis by clinical exomes. Am J Hum Genet, 2018, 103: 58-73.
28.	Shen F, Wang L, Liu H. Phenotypic analysis of clinical narratives using human phenotype ontology. Stud Health Technol Inform, 2017, 245: 581–5. [PubMed: 29295162].
29.	Kohler S, Schulz MH, Krawitz P, et al. Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am J Hum Genet, 2009, 85: 457-464.
30.	Zemojtel T, Kohler S, Mackenroth L, et al. Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Sci Transl Med, 2014, 6(252): 252ra123.
31.	Girdea M, Dumitriu S, Fiume M, et al. PhenoTips: patient phenotyping software for clinical and research use. Hum Mutat, 2013, 34: 1057-1065.
32.	Rosenow F, Akamatsu N, Bast T, Bauer S, Baumgartner C, Benbadis S, et al. Could the 2017 ILAE and the four-dimensional epilepsy classifications be merged to a new “Integrated Epilepsy Classification”?Seizure, 2020, 78(1): 31–37.
33.	Schulz MH, Kohler S, Bauer S, et al. Exact score distribution computation for ontological similarity searches. BMC Bioinformatics, 2011, 12: 441.
34.	R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. 2017. Available at:https://www.R-project.org.
35.	Wickham H, Averick M, Bryan J, et al. Welcome to the tidyverse. Journal of Open Source Software, 2019, 4(43): 1686.
36.	Greene D, Richardson S, Turro E. OntologyX: a suite of R packages for working with ontological data. Bioinformatics, 2017, 33: 1104-1106.
37.	Tudorache T, Nyulas C, Noy NF, et al. WebProtégé: A collaborative ontology editor and knowledge acquisition tool for the web. Semant Web, 2013, 4: 89-99.
38.	Trinka E, Cock H, Hesdorffer D, et al. A definition and classification of status epilepticus–Report of the ILAE Task Force on Classification of Status Epilepticus. Epilepsia, 2015, 56(5): 1515-1523.
39.	Chiang KL, Huang CY, Hsieh LP, et al. A propositional AI system for supporting epilepsy diagnosis based on the 2017 epilepsy classification: Illustrated by Dravet syndrome. Epilepsy Behav, 2020, 106: 107021.
40.	Sahoo SS, Lhatoo SD, Gupta DK, et al. Epilepsy and seizure ontology: towards an epilepsy informatics infrastructure for clinical research and patient care. J Am Med Inform Assoc, 2014, 21: 82-89.
41.	Kassahun Y, Perrone R, De Momi E, et al. Automatic classification of epilepsy types using ontology-based and genetics-based machine learning. Artif Intell Med, 2014, 61: 79-88.
42.	International League Against Epilepsy. EpilepsyDiagnosis. org. Available at:https:// www.epilepsydiagnosis.org.Accessed 10 Dec 2020.
43.	Pressler RM, Cilio MR, Mizrahi EM, et al. The ILAE classification of seizures and the epilepsies: Modification for seizures in the neonate. Position paper by the ILAE Task Force on Neonatal Seizures. Epilepsia, 2021, 62(3): 615-628.
44.	Nelson KB, Ellenberg JH. Predictors of epilepsy in children who have experienced febrile seizures. N Engl J Med, 1976, 295: 1029-1033.
45.	Steering Committee on Quality Improvement and Management, Subcommittee on Febrile Seizures American Academy of Pediatrics. Clinical practice guideline for the long-term management of the child with simple febrile seizures. Pediatrics, 2008, 121: 1281-1286.
46.	Scheffer IE, Berkovic SF. Generalized epilepsy with febrile seizures plus. A genetic disorder with heterogeneous clinical phenotypes. Brain, 1997, 120(Pt 3): 479–490.
47.	Uemura N, Okumura A, Negoro T, et al. Clinical features of benign convulsions with mild gastroenteritis. Brain Dev, 2002, 24: 745-749.
48.	Caraballo RH, Ganez L, Santos Cde L, et al. Benign infantile seizures with mild gastroenteritis: study of 22 patients. Seizure, 2009, 18: 686-689.
49.	Chen B, Cheng M, Hong S, et al. Clinical outcome of recurrent afebrile seizures in children with benign convulsions associated with mild gastroenteritis. Seizure, 2018, 60(1): 110-114.
50.	Engel JJr. A proposed diagnostic scheme for people with epileptic seizures and with epilepsy: report of the ILAE Task Force on Classification and Terminology. Epilepsia, 2001, 42(3): 796-803.

1. Helbig I, Riggs ER, Barry CA, et al. The ClinGen Epilepsy Gene Curation Expert Panel—Bridging the divide between clinical domain knowledge and formal gene curation criteria. Hum Mutat, 2018, 39(5): 1476-1484.
2. Greenberg DA, Subaran R. Blinders, phenotype, and fashionable genetic analysis: a critical examination of the current state of epilepsy genetic studies. Epilepsia, 2011, 52(1): 1-9.
3. Lhatoo SD, Bernasconi N, Blumcke I, et al. Big data in epilepsy: clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy. Epilepsia, 2020, 61(6): 1869-1883.
4. Scheffer IE, Berkovic S, Capovilla G, et al. ILAE classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia, 2017, 58(2): 512-521.
5. Fisher RS, Cross JH, D’Souza C, French JA, Haut SR, Higurashi N, et al. Instruction manual for the ILAE 2017 operational classification of seizure types. Epilepsia, 2017, 58(2): 531-542.
6. Fisher RS, Cross JH, French JA, et al. Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 2017, 58(2): 522-530.
7. Fisher RS, Acevedo C, Arzimanoglou A, Bogacz A, Cross JH, Elger CE, et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia, 2014, 55(2): 475-482.
8. Lüders H, Vaca GFB, Akamatsu N, et al. Classification of paroxysmal events and the four-dimensional epilepsy classification system. Epileptic Disord, 2019, 21(1): 1-29.
9. Blume WT, Luders HO, Mizrahi E, Tassinari C, Van Emde Boas W, Engel J. Glossary of descriptive terminology for ictal semiology: report of the ILAE Task Force on Classification and Terminology. Epilepsia, 2001, 42(4): 1212-1218.
10. Commission on Classification and Terminology of the International League Against Epilepsy. Proposal for revised clinical and electro-encephalographic classification of epileptic seizures. Epilepsia, 1981, 22(2): 489-501.
11. Berg AT, Berkovic SF, Brodie MJ, et al. Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005–2009. Epilepsia, 2010, 51(3): 676-685.
12. Lüders H, Acharya J, Baumgartner C, et al. Semiological seizure classification. Epilepsia, 1998, 39(4): 1006-1013.
13. Akawi N, McRae J, Ansari M, et al. Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4, 125 families. Nat Genet, 2015, 47(5): 1363-1369.
14. Turro E, Astle WJ, Megy K, et al. Whole-genome sequencing of patients with rare diseases in a national health system. Nature, 2020, 583(1): 96-102.
15. Lindy AS, Stosser MB, Butler E, et al. Diagnostic outcomes for genetic testing of 70 genes in 8565 patients with epilepsy and neurodevelopmental disorders. Epilepsia, 2018, 59(4): 1062-1071.
16. Truty R, Patil N, Sankar R, et al. Possible precision medicine implications from genetic testing using combined detection of sequence and intragenic copy number variants in a large cohort with childhood epilepsy. Epilepsia Open, 2019, 4(2): 397-408.
17. International League Against Epilepsy Consortium on Complex Epilepsies. Genome-wide megaanalysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies. Nat Commun, 2018, 9: 5269.
18. Epi25 Collaborative. Ultra-rare genetic variation in the epilepsies: a whole-exome sequencing study of 17, 606 individuals. Am J Hum Genet, 2019, 105: 267-282.
19. NHS Health Education England. Requesting whole genome sequencing: information for clinicians. Available at:https://www.genomicseducation.hee.nhs.uk/supporting-the-nhs-genomic medicine-service/requesting-whole-genome-sequencing-information-for-clinicians/.Accessed Dec 2020.
20. Gruber TR. A translation approach to portable ontology specifications. Knowledge Acquisition, 1993, 5: 199-220.
21. Kohler S, Gargano M, Matentzoglu N, et al. The human phenotype ontology in 2021. Nucleic Acids Res, 2021, 49: 1207-1217.
22. McKusick-Nathans Institute of Genetic Medicine JHUB, MD. Online Mendelian Inheritance in Man, OMIM®. Available at:https://omim.org/.Accessed 10 Dec 2020.
23. SNOMED International. SNOMED Clinical Terms. Available at:https://www.snomed.org/snomedct/sct-worldwide.Accessed 10 Dec 2020.
24. Helbig I, Lopez-Hernandez T, Shor O, et al. A recurrent missense variant in AP2M1 impairs clathrin-mediated endocytosis and causes developmental and epileptic encephalopathy. Am J Hum Genet, 2019, 104: 1060-1072.
25. Galer PD, Ganesan S, Lewis-Smith D, et al. Semantic similarity analysis reveals robust gene-disease relationships in developmental and epileptic encephalopathies. Am J Hum Genet, 2020, 107: 683-697.
26. Ganesan S, Galer PD, Helbig KL, et al. A longitudinal footprint of genetic epilepsies using automated electronic medical record interpretation. Genet Med, 2020, 22: 2060-2070.
27. Son JH, Xie G, Yuan C, et al. Deep phenotyping on electronic health records facilitates genetic diagnosis by clinical exomes. Am J Hum Genet, 2018, 103: 58-73.
28. Shen F, Wang L, Liu H. Phenotypic analysis of clinical narratives using human phenotype ontology. Stud Health Technol Inform, 2017, 245: 581–5. [PubMed: 29295162].
29. Kohler S, Schulz MH, Krawitz P, et al. Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am J Hum Genet, 2009, 85: 457-464.
30. Zemojtel T, Kohler S, Mackenroth L, et al. Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Sci Transl Med, 2014, 6(252): 252ra123.
31. Girdea M, Dumitriu S, Fiume M, et al. PhenoTips: patient phenotyping software for clinical and research use. Hum Mutat, 2013, 34: 1057-1065.
32. Rosenow F, Akamatsu N, Bast T, Bauer S, Baumgartner C, Benbadis S, et al. Could the 2017 ILAE and the four-dimensional epilepsy classifications be merged to a new “Integrated Epilepsy Classification”?Seizure, 2020, 78(1): 31–37.
33. Schulz MH, Kohler S, Bauer S, et al. Exact score distribution computation for ontological similarity searches. BMC Bioinformatics, 2011, 12: 441.
34. R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. 2017. Available at:https://www.R-project.org.
35. Wickham H, Averick M, Bryan J, et al. Welcome to the tidyverse. Journal of Open Source Software, 2019, 4(43): 1686.
36. Greene D, Richardson S, Turro E. OntologyX: a suite of R packages for working with ontological data. Bioinformatics, 2017, 33: 1104-1106.
37. Tudorache T, Nyulas C, Noy NF, et al. WebProtégé: A collaborative ontology editor and knowledge acquisition tool for the web. Semant Web, 2013, 4: 89-99.
38. Trinka E, Cock H, Hesdorffer D, et al. A definition and classification of status epilepticus–Report of the ILAE Task Force on Classification of Status Epilepticus. Epilepsia, 2015, 56(5): 1515-1523.
39. Chiang KL, Huang CY, Hsieh LP, et al. A propositional AI system for supporting epilepsy diagnosis based on the 2017 epilepsy classification: Illustrated by Dravet syndrome. Epilepsy Behav, 2020, 106: 107021.
40. Sahoo SS, Lhatoo SD, Gupta DK, et al. Epilepsy and seizure ontology: towards an epilepsy informatics infrastructure for clinical research and patient care. J Am Med Inform Assoc, 2014, 21: 82-89.
41. Kassahun Y, Perrone R, De Momi E, et al. Automatic classification of epilepsy types using ontology-based and genetics-based machine learning. Artif Intell Med, 2014, 61: 79-88.
42. International League Against Epilepsy. EpilepsyDiagnosis. org. Available at:https:// www.epilepsydiagnosis.org.Accessed 10 Dec 2020.
43. Pressler RM, Cilio MR, Mizrahi EM, et al. The ILAE classification of seizures and the epilepsies: Modification for seizures in the neonate. Position paper by the ILAE Task Force on Neonatal Seizures. Epilepsia, 2021, 62(3): 615-628.
44. Nelson KB, Ellenberg JH. Predictors of epilepsy in children who have experienced febrile seizures. N Engl J Med, 1976, 295: 1029-1033.
45. Steering Committee on Quality Improvement and Management, Subcommittee on Febrile Seizures American Academy of Pediatrics. Clinical practice guideline for the long-term management of the child with simple febrile seizures. Pediatrics, 2008, 121: 1281-1286.
46. Scheffer IE, Berkovic SF. Generalized epilepsy with febrile seizures plus. A genetic disorder with heterogeneous clinical phenotypes. Brain, 1997, 120(Pt 3): 479–490.
47. Uemura N, Okumura A, Negoro T, et al. Clinical features of benign convulsions with mild gastroenteritis. Brain Dev, 2002, 24: 745-749.
48. Caraballo RH, Ganez L, Santos Cde L, et al. Benign infantile seizures with mild gastroenteritis: study of 22 patients. Seizure, 2009, 18: 686-689.
49. Chen B, Cheng M, Hong S, et al. Clinical outcome of recurrent afebrile seizures in children with benign convulsions associated with mild gastroenteritis. Seizure, 2018, 60(1): 110-114.
50. Engel JJr. A proposed diagnostic scheme for people with epileptic seizures and with epilepsy: report of the ILAE Task Force on Classification and Terminology. Epilepsia, 2001, 42(3): 796-803.

Previous Article
癫痫发作期相关生物标志物的研究进展
Next Article
高龄老年患者颅内巨大脑膜瘤术后出现部分性运动发作一例并文献复习

Journal of Epilepsy

在人类表型本体论中对癫痫发作进行建模—根据当代ILAE概念使大的表型数据易于处理

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content