Risk-based analysis of test panels for carrier screening for monogenic disorders


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Abstract

A number of autosomal recessive diseases with well-known genetic markers are relatively common in the Russian Federation. The diagnostic effectiveness of test panels is traditionally based on the prevalence of determinable mutations, which is rather difficult to detect in heterogeneous populations. Objective: To evaluate the effectiveness of the screening panel for carriage of CFTR gene mutations in the Russian Federation using a risk-based approach. Materials and methods: Molecular genetic testing of blood samples of 1000 healthy donors was carried out by analyzing the 24 most frequent mutations in the CFTR gene using the real-time PCR with the analysis of melting profile. Results: The study found out 29 mutation carriers among 1000 healthy individuals. The total prevalence of detectable mutations was 2.9%. The vulnerability of the panel with a 95% probability is no more than 31%, which is close enough to the value of the vulnerability theoretically calculated basing on the prevalence of the mutations included (24.5). When using this panel (with the carriage of mutations in the CFTR gene), the risk of having an affected child in both partners will be only 1/170068, which is 17 times lower than the general population risk. Conclusion: Use of this screening panel in both partners may reduce the risk of affected offspring by 17 times, compared to the general population risk. Using a risk-based approach allowed us to effectively evaluate the vulnerability of the panel. If the incidence of the disease is known, this technique is applicable for any heterogeneous population.

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About the authors

Gaukhar Yu. Zobkova

Russian Medical Academy of Continuing Professional Education, Ministry of Health of Russia

Email: zobkova.dna@gmail.com
PhD student at the Department of Medical Genetics

Andrew E. Donnikov

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of Russia

Email: a_donnikov@oparina4.ru
Ph.D., Head of the Laboratory of Molecular Genetic Methods

Alexander N. Prytkov

Russian Medical Academy of Continuing Professional Education, Ministry of Health of Russia

PhD., Associate Professor, Senior Researcher at the Department of Medical Genetics

Natalia S. Demikova

Russian Medical Academy of Continuing Professional Education, Ministry of Health of Russia

Dr. Med. Sci., Professor, Head of the Department of Medical Genetics

Aligeidar A. Ragimov

I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia (Sechenov University)

Email: ra50@mail.ru
Dr. Med. Sci., Professor, Head of the Department of Intensive Care and Anesthesiology

References

  1. Gregg A.R. Expanded carrier screening. Obstet. Gynecol. Clin. North Am. 2018; 45(1): 103-12. https://dx.doi.org/10.1016/j.ogc.2017.10.005.
  2. Scott S.A., Edelmann L. Experience with carrier screening and prenatal diagnosis for 16 Ashkenazi Jewish genetic diseases. Hum. Mutat. 2010; 31(11): 1240-50. https://dx.doi.org/10.1002/humu.21327.
  3. ГОСТ Р. 51897-2011/Руководство ИСО 73:2009 Национальный стандарт Российской Федерации. Менеджмент риска. Термины и определения.
  4. Капранов Н.И., Каширская Н.Ю., ред. Муковисцидоз. M.: Медпрактика-М; 2014. 672 с.
  5. Воронкова А.Ю., Амелина Е.Л., Каширская Н.Ю., Кондратьева Е.И., Красовский С.А., Старинова М.А., Капранов Н.И., ред. Регистр больных муковисцидозом в Российской Федерации. 2017 год. М.: Медпрактика-М; 2019. 68 с.
  6. Kerem B., Rommens J.M., Buchanan J.A., Markiewicz D., Cox T.K., Chakravarti A. et al. Identification of the cystic fibrosis gene: genetic analysis. Science. 1989; 245(4922): 1073-80. https://dx.doi.org/10.1126/science.2570460.
  7. Watson M.S., Cutting G.R., Desnick R.J., Driscoll D.A., Klinger K., Mennuti M. et al. Cystic fibrosis population carrier screening: 2004 revision of American College of Medical Genetics mutation panel. Genet. Med. 2004; 6(5): 387-91. https://dx.doi.org/10.1097/01.gim.0000139506.11694.7c.
  8. American College of Obstetricians and Gynecologists Committee on Genetics. ACOG Committee Opinion No. 486: Update on carrier screening for cystic fibrosis. Obstet. Gynecol. 2011; 117(4): 1028-31. https://dx.doi.org/10.1097/ AOG.0b013e31821922c2.
  9. Castellani C., Macek M. Jr, Cassiman J.J., Duff A., Massie J., ten Kate L.P. et al. Benchmarks for cystic fibrosis carrier screening: a European consensus document. J. Cyst. Fibros. 2010; 9(3): 165-78. https://dx.doi.org/10.1016/j.jcf.2010.02.005.
  10. Zlotogora J. Population programs for the detection of couples at risk for severe monogenic genetic diseases. Hum. Genet. 2009; 126(2): 247-53. https://dx.doi.org/10.1007/s00439-009-0669-y.
  11. Massie J., Petrou V., Forbes R., Curnow L., Ioannou L., Dusart D. et al. Population-based carrier screening for cystic fibrosis in Victoria: the first three years experience. Aust. N. Z. J. Obstet. Gynaecol. 2009; 49(5): 484-9. https://dx.doi.org/10.1111/j.1479-828X.2009.01045.x.
  12. Castellani C., Picci L., Tamanini A., Girardi P., Rizzotti P., Assael B.M. Association between carrier screening and incidence of cystic fibrosis. JAMA. 2009; 302(23): 2573-9. https://dx.doi.org/10.1001/jama.2009.1758.
  13. Cunningham S., Marshall T. Influence of five years of antenatal screening on the paediatric cystic fibrosis population in one region. Arch. Dis. Child. 1998; 78: 345-8.
  14. Witt D., Wold C., Goonewardena P., Louie E., Rosenfeld S. Cystic fibrosis prenatal screening of 103,600 individuals in an HMO: molecular/clinical outcomes and a dramatic reduction in CF incidence. Proceedings of Annual Meeting, American Society of Human Genetics. Philadelphia, PA, USA; Nov 11-15, 2008. 686 (abstr.).
  15. Министерство здравоохранения и социального развития Российской Федерации. Приказ от 22.03.2006 № 185 «О массовом обследовании новорожденных детей на наследственные заболевания».
  16. Шерман В.Д., Каширская Н.Ю., Капранов Н.И. Современный алгоритм диагностики муковисцидоза. Педиатрия. Журнал им. Г.Н. Сперанского. 2014; 93(4): 68-74.
  17. Баранов А.А., Капранов Н.И., Каширская Н.Ю., Намазова-Баранова Л.С., Шерман В.Д., Симонова О.И., Томилова А.Ю., Савостьянов К.В., Пушков А.А., Владыкин А.Л., Шатохин Н.В. Проблемы диагностики муковисцидоза и пути их решения в России. Педиатрическая фармакология. 2014; 11(6): 16-23.
  18. Dodge J.A. A millennial view of cystic fibrosis. Dev. Period. Med. 2015; 19 (1): 9-13.
  19. Степанова А.А., Красовский С.А., Поляков А.В. Информативность поиска 19 частых мутаций в гене CFTR у российских больных муковисцидозом и расчетная частота заболевания в Российской Федерации. Генетика. 2016; 52(2): 231-41.
  20. Симакова Т.С., Брагин А.Г., Глушкова М.А., Петрова Н.В., Поляков А.В., Кондратьева Е.И., Шерман В.Д., Павлов А.Е. Опыт применения таргетного секвенирования для молекулярной диагностики муковисцидоза. Клиническая лабораторная диагностика. 2017; 62(5): 305-9. https://dx.doi.org/10.18821/0869-2084-2017-62-5-3-5-309.
  21. Литвинова М.М., Дадали Е.Л., Шевченко К.Г., Поляков А.В., Исаев А.А. Результаты генетического скрининга новорожденных на наличие наиболее частых наследственных заболеваний с аутосомно-рецессивным типом наследования. Клеточная трансплантология и тканевая инженерия. 2013; 8(3): 39-40.
  22. Гржибовский А.М., Иванов С.В., Горбатова М.А. Анализ номинальных и ранговых переменных данных с использованием программного обеспечения Statistica и SPSS. Наука и здравоохранение. 2016; 6. 5-39.

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