medalphabetМедицинский алфавитMedical alphabet2078-56312949-2807ООО «Альфмед»10.33667/2078-5631-2023-23-65-70medalphabet-3339Research ArticleСтатьиГенетическое тестирование в клинической лабораторной диагностике: настоящее и будущееGenetic testing in clinical laboratory diagnostics: Present and futureЩербоС. Н.ShcherboS. N.

Сергей Николаевич Щербо,  д. б. н., проф., зав. кафедрой

ФДПО

кафедра клинической лабораторной диагностики

Москва

Sergei N. Shcherbo, Dr Bio Sci (habil.), professor, head of Dept

Faculty of postgraduate education

Clinical Laboratory Diagnostics Dept

Moscow

https://orcid.org/0000-0002-0266-7015ЩербоД. С.ShcherboD. S.

Дмитрий Сергеевич Щербо, к. б. н., доцент, с. н. с.

Москва

Dmitry S. Shcherbo, PhD Bio, associate professor, senior researcher

Moscow

https://orcid.org/0000-0002-2738-2956НовиковА. А.NovikovA. A.

Александр Александрович Новиков, д. б. н., доцент, в. н. с.

ФДПО

кафедра клинической лабораторной диагностики

лаборатория клинической иммунологии

Москва

Alexander A. Novikov, DBio Sci (habil.), associate professor,  leading researcher

Faculty of postgraduate education

Clinical Laboratory Diagnostics Dept

Clinical Immunology Laboratory

Moscow

a.novikov@mknc.ruСавинаМ. И.SavinaM. I.

Марина Ивановна Савина, д. б. н., проф.

ФДПО

кафедра клинической лабораторной диагностики

Москва

Marina I. Savina, DBio Sci (habil.), professor

Faculty of postgraduate education

Clinical Laboratory Diagnostics Dept

Moscow

ТуркинаТ. И.TurkinaT. I.

Татьяна Ивановна Туркина, д. б. н., проф.

ФДПО

кафедра клинической лабораторной диагностики

Москва

Tatiana I. Turkina, DBio Sci (habil.), professor

Faculty of postgraduate education

Clinical Laboratory Diagnostics Dept

Moscow

ФГАОУ ВО «Российский Национальный Исследовательский Медицинский Университет имени Н. И. Пирогова» Минздрава РоссииРоссияRussian National Research Medical University n. a. N. I. PirogovRussian FederationФГАОУ ВО «Российский Национальный Исследовательский Медицинский Университет имени Н. И. Пирогова» Минздрава России; ГБУЗ «Московский клинический научно-практический центр имени А. С. Логинова Департамента здравоохранения Москвы»РоссияRussian National Research Medical University n. a. N. I. Pirogov; Moscow Clinical Scientific and Practical Centre n. a. A. S. LoginovRussian Federation202307112023023Современная лаборатория (2)6570Copyright © Щербо С.Н., Щербо Д.С., Новиков А.А., Савина М.И., Туркина Т.И., 20232023Щербо С.Н., Щербо Д.С., Новиков А.А., Савина М.И., Туркина Т.И.Shcherbo S.N., Shcherbo D.S., Novikov A.A., Savina M.I., Turkina T.I.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.med-alphabet.com/jour/article/view/3339

   Рассмотрены современное состояние и перспективы развития генетического тестирования в клинической лабораторной диагностике, современные форматы секвенирования нуклеиновых кислот, их достоинства и области применения. Несмотря на то что полногеномный анализ ассоциаций (GWAS) стал стандартной практикой в выявлении ОНП для определения предрасположенности к заболеваниям, отмечаются недостатки указанного подхода. Предлагается новый подход: интегративный полногеномный анализ ассоциаций (iGWAS), в котором используется информация об экспрессии генов для исследования взаимосвязи ОНП с фенотипом заболевания. Многочисленные исследования показали, что iGWAS позволяет существенно облегчить поиск генетических взаимосвязей и в этом плане превосходит метод, включающий только поиск ОНП. Проведение генетического тестирования будет способствовать реклассификации заболеваний человека на молекулярной основе. Описываются технические аспекты секвенирования с использованием нанопор, создание приложения для iPhone в качестве дополнения к миниатюрным устройствам для секвенирования и первого в мире мобильного анализатора геномных последовательностей iGenomics.

   Authors discuss the current state and prospects for the development of genetic testing in clinical laboratory diagnostics, recent nucleic acids sequencing technologies, their advantages and applications. Although genome-wide association studies (GWAS) have become a standard practice in identifying SNPs to determine disease susceptibility, this approach has limitations. A novel approach is proposed: integrative genome-wide association analysis (iGWAS), which relies on gene expression information to investigate the associations between SNPs and disease phenotype. Numerous studies have shown that iGWAS can significantly facilitate the search for genetic correlations and is superior to a method that relies only on the search for SNPs. Genetic testing will facilitate the molecular-based reclassification of human diseases. Authors describe the technical aspects of nanopore sequencing, the development of an iPhone app to complement miniature sequencing devices, and the world’s first mobile genomic sequence analyzer, iGenomics.

генетическое тестированиесеквенирование генома человекагенетические технологиитранскриптомgenetic testinghuman genome sequencinggenetic technologiestranscriptomeReferencesVan Dijk E. L., Jaszczyszyn Y., Naquin D. et al. The Third Revolution in Sequencing Technology. Trends Genet. 2018; 34 (9): 666–681. DOI: 10.1016/j.tig.2018.05.008.Van Dijk E. L., Jaszczyszyn Y., Naquin D. et al. The Third Revolution in Sequencing Technology. Trends Genet. 2018; 34 (9): 666–681. DOI: 10.1016/j.tig.2018.05.008.Goldfeder R. L., Priest J. R., Zook J. M. et al. Medical implications of technical accuracy in genome sequencing. Genome Medicine. 2016 (8): 1.Goldfeder R. L., Priest J. R., Zook J. M. et al. Medical implications of technical accuracy in genome sequencing. Genome Medicine. 2016 (8): 1.Nurk S., Koren S., Rhie A. et al. The complete sequence of a human genome. Science. 2022; 376, 6588: 44–53. DOI: 10.1126/science.abj6987.Nurk S., Koren S., Rhie A. et al. The complete sequence of a human genome. Science. 2022; 376, 6588: 44–53. DOI: 10.1126/science.abj6987.Aganezov S., Yan S. M., Soto D. C. et al. A complete reference genome improves analysis of human genetic variation. Science. 2022; 376, 6588. DOI: 10.1126/science.abl3533.Aganezov S., Yan S. M., Soto D. C. et al. A complete reference genome improves analysis of human genetic variation. Science. 2022; 376, 6588. DOI: 10.1126/science.abl3533.Gershman A., Sauria M. E.G., Guitart X. et al. Epigenetic patterns in a complete human genome. Science. 2022; 376, 6588. DOI: 10.1126/science.abj5089.Gershman A., Sauria M. E.G., Guitart X. et al. Epigenetic patterns in a complete human genome. Science. 2022; 376, 6588. DOI: 10.1126/science.abj5089.Altemose N., Logsdon G. F., Bzikadze A. V. et al. Complete genomic and epigenetic maps of human centromeres. Science. 2022; 376, 6588. DOI: 10.1126/science.abl4178.Altemose N., Logsdon G. F., Bzikadze A. V. et al. Complete genomic and epigenetic maps of human centromeres. Science. 2022; 376, 6588. DOI: 10.1126/science.abl4178.Hoyt S. J., Storer J. M. Hartley G. A. et al. From telomere to telomere: The transcriptional and epigenetic state of human repeat elements. Science. 2022; 376, 6588. DOI: 10.1126/science.abk3112.Hoyt S. J., Storer J. M. Hartley G. A. et al. From telomere to telomere: The transcriptional and epigenetic state of human repeat elements. Science. 2022; 376, 6588. DOI: 10.1126/science.abk3112.Rhie A, Nurk S, Cechova M. et al. The complete sequence of a human Y chromosome. Nature. 2023; 621, 7978: 344–354. DOI: 10.1038/s41586–023–06457-y.Rhie A, Nurk S, Cechova M. et al. The complete sequence of a human Y chromosome. Nature. 2023; 621, 7978: 344–354. DOI: 10.1038/s41586–023–06457-y.Lal A., Chiang Z. D., Yakovenko N., Duarte F. Deep learning-based enhancement of epigenomics data with AtacWorks. Nature Communications. 2021; 12, Article number: 1507.Lal A., Chiang Z. D., Yakovenko N., Duarte F. Deep learning-based enhancement of epigenomics data with AtacWorks. Nature Communications. 2021; 12, Article number: 1507.Pengfei Liu et al. Reanalysis of Clinical Exome Sequencing Data. N. Engl. J. Med. 2019; 380: 2478–2480.Pengfei Liu et al. Reanalysis of Clinical Exome Sequencing Data. N. Engl. J. Med. 2019; 380: 2478–2480.Bellcross C. A., Page P. Z., Meaney-Delman D. Direct-to-consumer personal genome testing and cancer risk prediction. Cancer J. 2012; 18, 4: 293–302.Bellcross C. A., Page P. Z., Meaney-Delman D. Direct-to-consumer personal genome testing and cancer risk prediction. Cancer J. 2012; 18, 4: 293–302.Sherry N. L., et al. Outbreak investigation using high-throughput genome sequencing within a diagnostic microbiology laboratory. J. Clin. Microbiol. 2013; 51, 5: 1396–1401.Sherry N. L., et al. Outbreak investigation using high-throughput genome sequencing within a diagnostic microbiology laboratory. J. Clin. Microbiol. 2013; 51, 5: 1396–1401.Sun S., Viller M., Wang Y. et al. Predicting embryonic aneuploidy rate in IVF patients using whole-exome sequencing. Human Genetics. 2022; 141: 1615–1627.Sun S., Viller M., Wang Y. et al. Predicting embryonic aneuploidy rate in IVF patients using whole-exome sequencing. Human Genetics. 2022; 141: 1615–1627.Huang Y-T, Lin X et al. iGWAS: Integrative Genome-Wide Association Studies of Genetic and Genomic Data for Disease Susceptibility Using Mediation Analysis. Genetic Epidemiology. 2015; 39, 5: 347–356.Huang Y-T, Lin X et al. iGWAS: Integrative Genome-Wide Association Studies of Genetic and Genomic Data for Disease Susceptibility Using Mediation Analysis. Genetic Epidemiology. 2015; 39, 5: 347–356.Replogle J. M., Saunders R. A., Pogson A. N. et al. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell. 2022; 185, 14: 2559–2575.Replogle J. M., Saunders R. A., Pogson A. N. et al. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell. 2022; 185, 14: 2559–2575.Schiabor Barrett S. et al. Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records. Genetics in Medicine. 2021; DOI: 10.1038/s41436–021–01293–9.Schiabor Barrett S. et al. Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records. Genetics in Medicine. 2021; DOI: 10.1038/s41436–021–01293–9.Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation. BMJ 2021; 372 doi: 10.1136/bmj.n214.Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation. BMJ 2021; 372 doi: 10.1136/bmj.n214.Jocelyn Kaiser. ‘The complexities are staggering.’ U.S. plans huge trial of blood tests for multiple cancers. Science Insider. 2022. DOI: 10.1126/science.add6151.Jocelyn Kaiser. ‘The complexities are staggering.’ U.S. plans huge trial of blood tests for multiple cancers. Science Insider. 2022. DOI: 10.1126/science.add6151.The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer. Posted Date: August 19th, 2020 doi: 10.21203/rs.3.rs-55052/v1.The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer. Posted Date: August 19th, 2020 doi: 10.21203/rs.3.rs-55052/v1.Gorzynski J. E. et al. Ultrarapid Nanopore Genome Sequencing in a Critical Care Setting. New England Journal of Medicine, January 2022. DOI: 10.1056/nejmc2112090.Gorzynski J. E. et al. Ultrarapid Nanopore Genome Sequencing in a Critical Care Setting. New England Journal of Medicine, January 2022. DOI: 10.1056/nejmc2112090.Schmidt J., Blessing F., Fimpler L. et al. Nanopore Sequencing in a Clinical Routine Laboratory: Challenges and Opportunities. Clin Lab. 2020 Jun 1; 66 (6). DOI: 10.7754/Clin.Lab.2019.191114.Schmidt J., Blessing F., Fimpler L. et al. Nanopore Sequencing in a Clinical Routine Laboratory: Challenges and Opportunities. Clin Lab. 2020 Jun 1; 66 (6). DOI: 10.7754/Clin.Lab.2019.191114.Palatnick A., Zhou B., Ghedin E., Schatz M. C. aiGenomics: Comprehensive DNA sequence analysis on your Smartphone. GigaScience, 2020; 9, 12, December 2020, giaa138. doi: 10.1093/gigascience/giaa138Palatnick A., Zhou B., Ghedin E., Schatz M. C. aiGenomics: Comprehensive DNA sequence analysis on your Smartphone. GigaScience, 2020; 9, 12, December 2020, giaa138. doi: 10.1093/gigascience/giaa138Muse E. D., Chen S-F., Liu Sh. et al. Impact of polygenic risk communication: An observational mobile application-based coronary artery disease study. NPJ Digital Medicine, 2022; 5, 30.Muse E. D., Chen S-F., Liu Sh. et al. Impact of polygenic risk communication: An observational mobile application-based coronary artery disease study. NPJ Digital Medicine, 2022; 5, 30.

The authors declare that there are no conflicts of interest present.