Characterization of mutations in the FBN1 gene and assessment of their pathogenic status in patients with Marfan syndrome

Background. Marfan syndrome (MS) is one of the frequently occurring diseases of the connective tissue dysplasia group, with a population prevalence of 2-3 cases per 10000 people. The life expectancy of patients is limited by lesions of the cardiovascular system. Diagnosis is based on the Ghent criteria (2010), in which the detection of a pathogenic mutation in the FBN1 gene is important. The gene, located on the 15th chromosome and containing 66 exons (65 of them coding), currently has more than 3000 nucleotide variants. Databases of pathogenic mutations are constantly updated with information about phenotypic manifestation of variants already described and those found for the first time.
Aim: to study the spectrum of mutations in the FBN1 gene in the Belarusian sample of patients with MS and to evaluate the diagnostic significance of the identified genetic variants.
Methods. The study included 21 unrelated patients with CM. To verify the diagnosis, sequencing of coding sequence was performed in all patients by NGS method. The found substitutions were confirmed by direct Sanger sequencing. The pathogenicity of the identified variants was assessed according to databases (ClinVar, HGMD) and criteria of the American Community of Medical Geneticists (ACMG, 2015).
Results. In 10 out of 21 (47.62 %) patients with clinical diagnosis of Marfan syndrome 10 rare variants of nucleotide sequence of FBN1 gene were detected, three (30 %) of which were detected for the first time. The interpretation of pathogenicity in the ClinVar and HGMD databases differed significantly. Only one of the 7 previously described variants is listed as a pathogenic mutation in both databases (ClinVar, HGMD), 3 variants had uncertain clinical significance (VUS, class III) in the ClinVar database, with one of them (p.Cys1159Tyr) described as diagnostically significant in HGMD (DM, class IV-V). The variant p.Asp2291Gly, represented as VUS in ClinVar, and the replacement p.Cys2674Tyr, pathogenic in ClinVar, were absent in the HGMD database, and the variant p.Cys1956Arg, diagnostically significant in the HGMD database, was not present in ClinVar. The previously described variant p.Cys2617TrpfsTer65 is currently not registered in either database. The variant p.Thr1020Ala was identified as VUS in both bases and was characterized by the most favorable course of the disease. Three variants were detected for the first time and are pathogenic according to ACMG criteria: c.3838G>C (p.Asp1280His), c.7694G>C (p.Cys2565Ser), c.7849T>C (p.Cys2617Arg). The paper provides a detailed description of the phenotypic manifestation of the new mutations. Most of the pathogenic mutations were located in exons 62 and 64.
Conclusions. Ten rare variants in the FBN1 gene were detected, 9 of which were pathogenic according to the ACMG criteria (2015). For 4 (40%) variants the data in ClinVar and HGMD databases differed. The data obtained indicate the need to clarify the interpretation of pathogenicity of some variants in the FBN1 gene. The use of data from the two databases allowed us to confirm the pathogenic status for a significantly larger number of variants. Three new missense variants were pathogenic by in silico predictors and led to a severe course of MS, indicating their diagnostic significance.

1. Faivre L.C., Collod-Beroud G, Loeys BL et al. Effect of mutation type and location on clinical outcome in 1,013 probands with Marfan syndrome or related phenotypes and FBN1 mutations: an international study. The American Journal of Human Genetics. 2007; 81(3): 454-466.

2. Delyagin V.M., Zhakupova ZH.S., Narycheva I.A., Melnikova M.B. Sindrom Marfana (printsipy diagnostiki, klinicheskaya kartina, taktika vracha) [Marfan syndrome (principles of diagnosis, clinical picture, doctor’s tactics)]. Prakticheskaya meditsina [Practical medicine]. 2008; 4 (28): 39-43. (In Russ.)

3. Groth K.A., Stochholm K., Hove H. et al. Causes of mortality in the Marfan syndrome (from a Nationwide Register Study). The American journal of cardiology. 2018;122(7):1231-1235.

4. Isekame Y., Gati S., Aragon-Martin J.A., et al. Cardiovascular Management of Adults with Marfan Syndrome. Eur Cardiol. 2016;11(2):102-110.

5. Loeys B.L., Dietz H.C., Braverman A.C. et al. The revised Ghent nosology for the Marfan syndrome. Journal of medical genetics. 2010; 47(7): 476-485.

6. Gusina A.A., Stalybko N.S., Krinitskaya K.A., et al. Mutatsii v gene FBN1 u patsiyentov s vrozhdennym podvyvikhom khrustalika pri sindrome Marfana [FBN1 gene mutations in patients with congenital ectopia lentis caused by Marfan syndrome]. Izvestiya Natsional’noy akademii nauk Belarusi. Seriya meditsinskikh nauk [Proceedings of the National Academy of Sciences of Belarus, Medical series]. 2020;17(1):87-100. (In Russ.)

7. Rogozhina Yu.A., Rumyantseva V.A., Bukaeva A.A., Zaklyazminskaya E.V. DNK-diagnostika i spektr mutatsiy v gene FBN1 pri sindrome Marfana [DNA diagnostics and mutation spectrum of the gene FBN1 in Marfan’s syndrome]. Rossiyskiy kardiologicheskiy zhurnal [Russian Journal of Cardiology]. 2015;(10):61-64. (In Russ.)

8. Mathew C.G. The isolation of high molecular weight eucaryotic DNA. Methods Mol Biol. 1985; 2: 31-4.

9. Wang K., Li M., Hakonarson H., ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010 Sep; 38(16): 164.

10. Stenson P.D., Mort M., Ball E.V. et al. The Human Gene Mutation Database (HGMD): optimizing its use in a clinical diagnostic or research setting. Hum Genet. 2020 Oct;139(10):1197-1207.

11. Landrum M.J., Chitipiralla S., Brown G.R. et al. ClinVar: improvements to accessing data. Nucleic Acids Res. 2020;48(1):835-844.

12. Adzhubei I.A., Schmidt S., Peshkin L. et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4): 248-9.

13. Ioannidis N.M., Rothstein J.H., Pejaver V. et al. REVEL: An ensemble method for predicting the pathogenicity of rare missense variants. Am J Hum Genet. 2016 Oct 6; 99(4):877-885.

14. Shihab H.A., Gough J., Cooper D.N. et al. Predicting the Functional, Molecular and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models. Hum Mutat. 2013;34(1):57- 65.

15. Kumar P., Henikoff S., Ng P.C. Predicting the effects of coding nonsynonymous variants on protein function using the SIFT algorithm. Nat Protoc. 2009; 4(7):1073-81.

16. UniProt Consortium. UniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Res. 2023;51(1):523-531.

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 Med. 2015;17(5):405-23.

18. Tjeldhorn L., Amundsen S.S., Barøy T. et al. Qualitative and quantitative analysis of FBN1 mRNA from 16 patients with Marfan Syndrome. BMC Medical Genetic. 2015;16: 1-8.

19. Tan L., Zongze L., Chengming Z. et al. FBN1 mutations largely contribute to sporadic non-syndromic aortic dissection. Human Molecular Genetics. 2017; 26(24): 4814-4822.

20. Zhang M.Q. Statistical features of human exons and their flanking regions. Human molecular genetics. 1998; 7(5): 919-932.

21. Stheneur C., Gwenaëlle C., Laurence F. et al. Identification of the minimal combination of clinical features in probands for efficient mutation detection in the FBN1 gene. European Journal of Human Genetics. 2009; 17(9): 1121-1128.

22. Comeglio P., Johnson P., Arno G. et al. The importance of mutation detection in Marfan syndrome and Marfan-related disorders: Report of 193 FBN1 mutations. Human mutation. 2007; 28(9): 928-928.

23. Chen S., Francioli L.C., Goodrich J.K. et al. A genome-wide mutational constraint map quantified from variation in 76,156 human genomes. Nature. 2022; 625(7993):92-100.

24. National Center for Biotechnology Information (NCBI)[Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; [1988] – [cited 2023 July 16]. Available from: https://www.ncbi.nlm.nih.gov.

25. Rand-Hendriksen S., Tjeldhorn L., Lundby R. et al. Search for correlations between FBN1 genotype and complete Ghent phenotype in 44 unrelated Norwegian patients with Marfan syndrome. Am J Med Genetka. 2007 Sep 1;143(17):1968-77.

26. Baudhuin L.M., Kluge M.L., Kotzer K.E. et al. Variability in genebased knowledge impacts variant classification: an analysis of FBN1 missense variants in ClinVar. European Journal of Human Genetics. 2019; 27(10): 1550-1560.

27. National Center for Biotechnology Information. ClinVar; [VCV000451315.2], https://www.ncbi.nlm.nih.gov/clinvar/variation/VCV000451315.2 (accessed Jan. 14, 2024)

28. Chen Z.X., Jia W.N., Jiang Y.X. Genotype-phenotype correlations of marfan syndrome and related fibrillinopathies: Phenomenon and molecular relevance. Front Genet. 2022 Aug 16;13:943083.

29. Buratti E., Chivers M., Královicová J. et al. Aberrant 5′ splice sites in human disease genes: mutation pattern, nucleotide structure and comparison of computational tools that predict their utilization. Nucleic acids research. 2007; 35(13): 4250-4263.

30. Groth K.A., Kodolitsch Y.V., Kutsche K. et al. Evaluating the quality of Marfan genotype–phenotype correlations in existing FBN1 databases. Genetics in Medicine. 2017; 19(7): 772-777.

31. Madam L., Szakszon K., Pfliegler G. et al. FBN1 gene mutations in 26 Hungarian patients with suspected Marfan syndrome or related fibrillinopathies. Journal of biotechnology. 2019; 301: 105-111.

32. Renner S., Schüler H., Alawi M. et al. Next-generation sequencing of 32 genes associated with hereditary aortopathies and related disorders of connective tissue in a cohort of 199 patients. Genetics in Medicine. 2019; 21(8): 1832-1841.

33. Waldmüller S., Müller M., Warnecke H. et al. Genetic testing in patients with aortic aneurysms/dissections: a novel genotype/phenotype correlation. European Journal of cardio-thoracic Surgery. 2007; 31(6): 970-975.

34. Evangelisti L., Lucarini L., Attanasio M. et al. A single heterozygous nucleotide substitution displays two different altered mechanisms in the FBN1 gene of five Italian Marfan patients. European journal of medical genetics. 2010; 53(5): 299-302.

35. National Center for Biotechnology Information. ClinVar; [VCV000581358.1], https://www.ncbi.nlm.nih.gov/clinvar/variation/VCV000581358.1 (accessed Jan. 14, 2024).

36. Tiecke F., Katzke S., Booms P. et al. Classic, atypically severe and neonatal Marfan syndrome: twelve mutations and genotype–phenotype correlations in FBN1 exons 24–40. European Journal of Human Genetics. 2001; 9(1): 13-21.

37. Attanasio M., Lapini I., Evangelisti L. et al. FBN1 mutation screening of patients with Marfan syndrome and related disorders: detection of 46 novel FBN1 mutations. Clinical genetics. 2008; 74(1): 39-46.

38. Wooderchak-Donahue W., VanSant-Webb C., Tvrdik T. et al. Clinical utility of a next generation sequencing panel assay for Marfan and Marfan-like syndromes featuring aortopathy. American Journal of Medical Genetics. 2015; 167(8): 1747-1757.

39. Girdauskas E., Geist L., Disha K. et al. Genetic abnormalities in bicuspid aortic valve root phenotype: preliminary results. European Journal of Cardio-thoracic Surgery. 2017; 52(1): 156-162.

40. Giorgio E., Brussino A., Biamino E. et al. Exome sequencing in children of women with skewed X-inactivation identifies atypical cases and complex phenotypes. European Journal of Paediatric Neurology. 2017; 21(3): 475-484.