Role of molecular genetic factors in formation of the clinical type of neurofibromatosis type 2

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Resumo

Neurofibromatosis type 2 is a hereditary disease with predisposition to the development of multiple tumors of the central and peripheral nervous system. The disease is characterized by significant variability in the clinical picture; the number of neoplasms, their location and growth rate largely determine the severity of the course. However, assessing the rate of tumor growth requires the availability of a consistent series of instrumental studies conducted within a certain time range, which is not always available at the time of initial treatment. In this study, based on quantitative (age of onset, age of examination) and qualitative (large number of intracranial tumors, large number of spinal tumors, severity of neurological symptoms, mosaic status of the genetic variant) characteristics, an alternative classification of clinical subtypes of neurofibromatosis type 2 was developed. We have revealed statistically significant differences (p-value = 0.037) in the representation of Halliday prognostic classes between the groups identified using the proposed classification which allows us to suggest the possibility of integrating this approach into clinical practice.

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Sobre autores

K. Karandasheva

Research Centre for Medical Genetics

Autor responsável pela correspondência
Email: vstrel@list.ru
Rússia, Moscow, 115522

E. Makashova

Burdenko National Medical Research Center of Neurosurgery; Loginov Moscow Clinical Scientific Center

Email: vstrel@list.ru
Rússia, Moscow, 125047; Moscow, 111123

F. Ageeva

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

K. Anoshkin

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

P. Sparber

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

A. Borovikov

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

P. Vasiluev

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

M. Pashchenko

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

A. Tanas

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

V. Strelnikov

Research Centre for Medical Genetics

Email: vstrel@list.ru
Rússia, Moscow, 115522

Bibliografia

  1. Coy S., Rashid R., Stemmer-Rachamimov A., Santagata S. An update on the CNS manifestations of neurofibromatosis type 2 // Acta Neuropathologica. 2020. V. 139. P. 643–665. https://doi.org/10.1007/s00401-019-02029-5
  2. Eldridge R., Parry D.M., Kaiser-Kupfer M.I. Neurofibromatosis 2 (NF2): Clinical heterogeneity and natural history based on 39 individuals in 9 families and 16 sporadic cases // Am. J. Hum. Genet.1991. V. 49. № 4. P. 133–133.
  3. Evans D.G., Huson S.M., Donnai D. et al. A genetic study of type 2 neurofibromatosis in the United Kingdom. I. Prevalence, mutation rate, fitness, and confirmation of maternal transmission effect on severity // J. Med. Genet. 1992. V. 29. № 12. P. 841–846. https://doi.org/10.1136/jmg.29.12.841
  4. Ragge N.K. Clinical and genetic patterns of neurofibromatosis 1 and 2 // British J. Ophthalmology. 1993. V. 77. № 10. P. 662–672.
  5. Parry D.M., Eldridge R., Kaiser-Kupfer M.I. et al. Neurofibromatosis 2 (NF2): Clinical characteristics of 63 affected individuals and clinical evidence for heterogeneity // Am. J. Med. Genet. 1994. V. 52. № 4. P. 450–461. https://doi.org/10.1002/ajmg.1320520411
  6. Ruttledge M.H., Andermann A.A., Phelan C.M. et al. Type of mutation in the neurofibromatosis type 2 gene (NF2) frequently determines severity of disease // Am. J. Med. Genet. 1996. V. 59. № 2. P. 331–342.
  7. Baser M.E., Kuramoto L., Woods R. et al. The location of constitutional neurofibromatosis 2 (NF2) splice site mutations is associated with the severity of NF2 // J. Med. Genet. 2005. V. 42. № 7. P. 540–546. https://doi.org/10.1136/jmg.2004.029504
  8. Baser M.E., Wallace A.J., Strachan T., Evans D.G. Clinical and molecular correlates of somatic mosaicism in neurofibromatosis 2 // J. Med. Genet. 2000. V. 37. № 7. P. 542–543. https://doi.org/10.1136/jmg.37.7.542
  9. Selvanathan S.K., Shenton A., Ferner R. et al. Further genotype–phenotype correlations in neurofibromatosis 2 // Clin. Genet. 2010. V. 77. № 2. P. 163–170. https://doi.org/10.1111/j.1399-0004.2009.01315.x
  10. Halliday D., Emmanouil B., Pretorius P. et al. Genetic Severity Score predicts clinical phenotype in NF2 // J. Med. Genet. 2017. V. 54. № 10. P. 657–664. https://doi.org/10.1136/jmedgenet-2017-104519
  11. Bettegowda C., Upadhayaya M., Evans D.G. et al. Genotype-phenotype correlations in neurofibromatosis and their potential clinical use // Neurology. 2021. V. 97. № 7. Suppl. 1. P. S91–S98. https://doi.org/10.1212/WNL.0000000000012436
  12. Ahlawat S., Fayad L.M., Khan M.S. et al. Current whole-body MRI applications in the neurofibromatoses: NF1, NF2, and schwannomatosis // Neurology. 2016. V. 87. № 7. Suppl 1. P. S31–S39. https://doi.org/10.1212/WNL.0000000000002929
  13. Gugel I., Grimm F., Teuber C. et al. Management of NF2-associated vestibular schwannomas in children and young adults: Influence of surgery and clinical factors on tumor volume and growth rate // J. Neurosurgery: Pediatrics. 2019. V. 24. № 5. P. 584–592. https://doi.org/10.3171/2019.6.PEDS1947
  14. Baser M.E., Friedman J.M., Joe H. et al. Empirical development of improved diagnostic criteria for neurofibromatosis 2 // Genet. in Medicine. 2011. V. 13. № 6. P. 576–581. https://doi.org/10.1097/GIM.0b013e318211faa9
  15. Evans D.G. Neurofibromatosis type 2 // Handbook Clin. Neurology. 2015. V. 132. P. 87–96. https://doi.org/10.1016/B978-0-444-62702-5.00005-6 github.com/kkarandasheva/AmpliSep
  16. Рыжкова О.П., Кардымон О.Л., Прохорчук Е.Б. и др. Руководство по интерпретации данных последовательности ДНК человека, полученных методами массового параллельного секвенирования (MPS) (редакция 2018, версия 2) // Мед. генетика. 2019. Т. 18. № 2. С. 3–23. https://doi.org/10.25557/2073-7998.2019.02.3-23
  17. Richards S., Aziz N., Bale S. et al. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology // Genet. in Medicine. 2015. V. 17. №. 5. P. 405–423 https://doi.org/10.1038/gim.2015.30
  18. Lê S., Josse J., Husson F. FactoMineR: An R package for multivariate analysis // J. Stat. Software. 2008. V. 25. P. 1–18. https://doi.org/10.18637/jss.v025.i01
  19. Josse J., Husson F. missMDA: A package for handling missing values in multivariate data analysis // J. Stat. Software. 2016. V. 70. P. 1–31. https://doi.org/10.18637/jss.v070.i01 https://cran.r-project.org/package=factoextra
  20. Wickham H. ggplot2: Elegant Graphics for Data Analysis. N. Y.: Springer-Verlag. 2016. 213 p. ISBN 978-3-319-24277-4 https://CRAN.R-project.org/package=ggpubr
  21. Godel T., Bäumer P., Farschtschi S. et al. Peripheral nervous system alterations in infant and adult neurofibromatosis type 2 // Neurology. 2019. V. 93. №. 6. P. e590–e598. https://doi.org/10.1212/WNL.0000000000007898
  22. Louvrier C., Pasmant E., Briand-Suleau A. et al. Targeted next-generation sequencing for differential diagnosis of neurofibromatosis type 2, schwannomatosis, and meningiomatosis // Neuro-Oncology. 2018. V. 20. № 7. P. 917-929. https://doi.org/110.1093/neuonc/noy009

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2. Fig. 1. Age characteristics of the study sample and results of molecular genetic testing. a – distribution of age of clinical onset (green) and age at examination (yellow) in the study sample, segment length corresponds to the duration of the disease; b – distribution density of the duration of the disease; c – frequency of occurrence of different types of mutations in the study sample, including germline (orange) and mosaic (blue) genetic variants; d – frequency of familial and sporadic cases, including germline (orange) and mosaic (blue) genetic variants.

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3. Fig. 2. FAMD of clinical features of the sample (age of onset, age at examination, severity of neurological symptoms, presence of more than 10 intracranial tumors, presence of more than 10 tumors in the spinal cord (SC), representation of the mutation in the body). a – each point corresponds to a patient, separate panels characterize sample (1) by the presence of more than 10 intracranial tumors, sample (2) – by the presence of more than 10 tumors in the spinal cord, (3) – by the representation of the pathogenic allele in the body, (4) – by the severity of the neurological status. Gray dots correspond to the absence of information on a specific feature; b, c – the contribution of the studied features to dimensions 1 and 2; d, e – the position of the features in the projection coordinates.

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4. Fig. 3. Comparison of the selected groups of tumor prevalence. a – FAMD of clinical features of the sample. Red color corresponds to group 1, yellow – to group 2, blue – to group 3. The square shape of the marker corresponds to a patient with a germline mutation, the round one – to a mosaic one; b – distribution of the age of onset in the selected groups; c – distribution of the age of examination in the selected groups; d – age of clinical onset, age of examination, duration of the disease for different categories according to Halliday in the selected groups. The orange square marker corresponds to germline variants, the blue round one – to mosaic ones.

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