BIOINFORMATIC ANALYSIS OF SINGLE NUCLEOTIDE VARIANTS IN THE F12 GENE ASSOCIATED WITH HEREDITARY ANGIOEDEMA

Abstract

Hereditary angioedema (HAE) is a genetically determined disorder classified as a primary immunodeficiency involving complement system dysfunction. In most patients, the disease is characterized by a deficiency of C1 inhibitor (type I HAE) or impaired functional activity of the C1 inhibitor (type II HAE). In such cases, the diagnosis is based on laboratory findings. In HAE with normal C1 inhibitor levels and activity, the diagnosis can only be established based on family history and/or genetic testing. Among patients with HAE with normal C1 inhibitor, mutations in the F12 gene are most frequently observed, particularly in women. However, mutations with uncertain clinical significance are often identified. Given the limited number of HAE cases, it is not feasible to experimentally determine the clinical relevance of newly discovered polymorphic variants. A potential solution to this problem is the in silico analysis of each novel polymorphism.

The aim of our study was to evaluate the predictive potential of bioinformatic analysis methods in assessing polymorphic variants in the F12 gene.

The study focused on four polymorphic variants — NC_000005.9:g.176831285C>G, NC_000005.9:g.176831258C>G, NC_000005.9:g.176831232G>C, and NC_000005.9:g.176831232G>T — with varying clinical significance statuses. To predict the effect of these polymorphic variants on the F12 protein, various web-based tools employing different algorithms were used, including SIFT, PolyPhen-2, FATHMM-XF, MutationTaster2021, MutPred2, MUpro, I-Mutant 2, HOPE, and ChimeraX.

Results. In silico analysis demonstrated that the mutations NC_000005.9:g.176831232G>C (p.Thr328Arg) and NC_000005.9:g.176831232G>T (p.Thr328Lys) have a pathogenic effect, which is fully consistent with their previously established clinical status. At the same time, the polymorphic variants NC_000005.9:g.176831258C>G (p.Gln319His) and NC_000005.9:g.176831285C>G (p.Arg310Ser) do not appear to be independent causes of the disease, although their potential role in modifying the clinical phenotype cannot be excluded.

Bioinformatic analysis plays a key role in the preliminary assessment of the significance of newly identified mutations in the F12 gene and facilitates a more precise identification of pathogenic variants. The integration of bioinformatic tools into diagnostic workflows is essential for determining the cause of disease in patients with hereditary angioedema who present with normal levels and functional activity of C1 inhibitor.

1. Pechnikova N.A., Ostankova Y.V., Liubimova N.E., Semenov A.V., Kuznetsova R.N., Totolian A.A. Application of bioinformatic analysis to identify the clinical significance of missense mutations in the HS3ST6 gene in the development of hereditary angioedema. Infektsiya i immunitet = Russian Journal of Infection and Immunity, 2022, Vol. 12, no. 5, pp. 997–1005. doi: 10.15789/1563-0625-AOB-2579.

2. Pechnikova N.A., Ostankova Y.V., Liubimova N.E., Semenov A.V., Kuznetsova R.N., Totolian A.A. Application of bioinformatic analysis to identify the clinical significance of missense mutations in the HS3ST6 gene in the development of hereditary angioedema. Infektsiya i immunitet = Russian Journal of Infection and Immunity, 2022, Vol. 12, no. 5, pp. 997–1005. doi: 10.15789/1563-0625-ABA-2577.

3. Russian Association of Allergologists and Clinical Immunologists, National Association of Experts in Primary Immunodeficiencies. Primary Immunodeficiencies with Predominant Antibody Deficiency: Clinical Guidelines. – 2022.

4. Russian Association of Allergologists and Clinical Immunologists, Union of Pediatricians of Russia, Association of Medical Geneticists, National Association of Experts in Primary Immunodeficiencies. Clinical Guidelines: Hereditary Angioedema. – 2024.

5. Adzhubei I.A., Schmidt S., Peshkin L., Ramensky V.E., Gerasimova A., Bork P., Kondrashov A.S., Sunyaev S.R. A method and server for predicting damaging missense mutations. Nat. Methods, 2010, Vol. 7, no. 4, pp. 248–249.

6. Beer N.L., Osbak K.K., van de Bunt M., Tribble N.D., Steele A.M., Wensley K.J., Gloyn A.L. Insights into the pathogenicity of rare missense GCK variants from the identification and functional characterization of compound heterozygous and double mutations inherited in cis. Diabetes Care, 2012, Vol. 35, no. 7, pp. 1482–1484. doi: 10.2337/dc11-2420

7. Bork K., Wulff K., Meinke P., Wagner N., Hardt J., Witzke G. A novel mutation in the coagulation factor 12 gene in subjects with hereditary angioedema and normal C1-inhibitor. Clin. Immunol., 2011, Vol. 141, no. 1, pp. 31–35. doi: 10.1016/j.clim.2011.07.002

8. Busse P.J., Christiansen S.C., Riedl M.A., Banerji A., Bernstein J.A., Castaldo A.J., Craig T.J., Davis-Lorton M., Frank M.M., Gower R.G. US HAEA Medical Advisory Board 2020 Guidelines for the Management of Hereditary Angioedema. J. Allergy Clin. Immunol. Pract., 2021, Vol. 9, no. 1, pp. 132–150. doi: 10.1016/j.jaip.2020.08.046

9. Camilli F., Borrmann A., Gholizadeh S., te Beek T.A.H., Kuipers R.K.P., Venselaar H. The future of HOPE: what can and cannot be predicted about the molecular effects of a disease causing point mutation in a protein? EMBnet.journal, 2011, Vol. 17, no. 1, pp. 1–10. doi: 10.14806/ej.17.1.212

10. Capriotti E., Fariselli P., Casadio R. I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res., 2005, Vol. 33, suppl_2, pp. 306–310. doi: 10.1093/nar/gki375

11. Cheng J., Randall A., Baldi P. Prediction of protein stability changes for single-site mutations using support vector machines. Proteins, 2006, Vol. 62, no. 4, pp. 1125–1132. doi: 10.1002/prot.20810

12. Cohn D.M., Renné T. Targeting factor XIIa for therapeutic interference with hereditary angioedema. J. Intern. Med., 2024, Vol. 296, no. 4, pp. 311–326. doi: 10.1111/joim.20008

13. Depetri F., Tedeschi A., Cugno M. Angioedema and emergency medicine: From pathophysiology to diagnosis and treatment. Eur. J. Intern. Med., 2019, Vol. 59, pp. 8–13. doi: 10.1016/j.ejim.2018.09.004

14. Dewald G., Bork K. A missense mutation in the factor XII gene in a family with hereditary angioedema. Biochem. Biophys. Res. Commun., 2006, Vol. 343, no. 4, pp. 1286–1289. doi: 10.1016/j.bbrc.2006.03.092

15. Itan Y., Shang L., Boisson B., Ciancanelli M.J., Markle J.G., Martinez-Barricarte R., Scott E., Shah I., Stenson P.D., Gleeson J., et al. The mutation significance cutoff: gene-level thresholds for variant predictions. Nat. Methods, 2016, Vol. 13, no. 2, pp. 109–110. doi: 10.1038/nmeth.3739

16. Lucena-Aguilar G., Sanchez- Ivanov I., Matafonov A., Sun M.F., Cheng Q., Dickeson S.K., Verhamme I.M., Gailani D. Proteolytic properties of single-chain factor XII: a mechanism for triggering contact activation. Blood, 2017, Vol. 129, no. 11, pp. 1527–1537. doi: 10.1182/blood-2016-10-744110

17. Liao S.M., Du Q.S., Meng J.Z., Pang Z.W., Huang R.B. The multiple roles of histidine in protein interactions. Chem. Cent. J., 2013, Vol. 7, Article no. 44, pp. 1–12. doi: 10.1186/1752-153X-7-44

18. Liu J., Qin J., Borodovsky A., Racie T., Castoreno A., Schlegel M., Maier M.A., Zimmerman T., Fitzgerald K., Butler J., Akinc A. An investigational RNAi therapeutic targeting Factor XII (ALN-F12) for the treatment of hereditary angioedema. RNA, 2019, Vol. 25, no. 2, pp. 255–263. doi: 10.1261/rna.068916.118

19. Manto I.A., Latysheva E.A., Sorokina L.E., Latysheva T.V. The place of scales and questionnaires in assessing the disease’s severity and the long-term prophylaxis’s prescribing in patients with hereditary angioedema. Terapevt. Arkh., 2021, Vol. 93, no. 12, pp. 1498–1509. https://doi.org/10.26442/00403660.2021.12.201294

20. Meng E.C., Goddard T.D., Pettersen E.F., Couch G.S., Pearson Z.J., Morris J.H., Ferrin T.E. UCSF ChimeraX: Tools for structure building and analysis. Protein Sci., 2023, Vol. 32, no. 11, pp 23-38. doi: 10.1002/pro.4792

21. Motta G., Juliano L., Shariat-Madar Z. Kallikrein-kinin system: insights into a multifunctional system. Front. Physiol., 2023, Vol. 14, Article no. 1305981. doi: 10.3389/fphys.2023.1305981

22. Mottaz A., David F.P.A., Veuthey A.L., Yip Y.L. Easy retrieval of single amino-acid polymorphisms and phenotype information using SwissVar. Bioinformatics, 2010, Vol. 26, no. 6, pp. 851–852. doi: 10.1093/bioinformatics/btq028

23. Ng P.C., Henikoff S. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res., 2003, Vol. 31, no. 13, pp. 3812–3814. doi: 10.1093/nar/gkg509

24. Pac M., Bernatowska E. Comprehensive activities to increase recognition of primary immunodeficiency and access to immunoglobulin replacement therapy in Poland. Eur. J. Pediatr., 2016, Vol. 175, pp. 1099–1105. doi: 10.1007/s00431-016-2746-2

25. Pathak M., Wilmann P., Awford J., Li C., Hamad B.K., Fischer P.M., Emsley J. Coagulation factor XII protease domain crystal structure. J. Thromb. Haemost., 2015,Vol. 13, no. 4, pp. 580–591. doi: 10.1111/jth.12849

26. Pejaver V., Urresti J., Lugo-Martinez J., Pagel K.A., Lin G.N., Nam H.J., Mort M., Cooper D.N., Sebat J., Iakoucheva L.M., et al. Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nat. Commun., 2020, Vol. 11, Article no. 5918. doi: 10.1038/s41467-020-19669-x

27. Rentzsch P., Witten D., Cooper G.M., Shendure J., Kircher M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res., 2019, Vol. 47, D1, pp. 886–894. doi: 10.1093/nar/gky1016

28. Rogers M.F., Shihab H.A., Mort M., Cooper D.N., Gaunt T.R., Campbell C. FATHMM-XF: accurate prediction of pathogenic point mutations via extended features. Bioinformatics, 2018, Vol. 34, no. 3, pp. 511–513. doi: 10.1093/bioinformatics/btx536

29. Shamanaev A., Dickeson S.K., Ivanov I., Litvak M., Sun M.F., Kumar S., Gailani D. Mechanisms involved in hereditary angioedema with normal C1-inhibitor activity. Front. Physiol., 2023, Vol. 14, Article no. 1146834. doi: 10.3389/fphys.2023.1146834

30. Sherry S.T., Ward M.H., Kholodov M., Baker J., Phan L., Smigielski E.M., Sirotkin K. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res., 2001, Vol. 29, no. 1, pp. 308–311. doi: 10.1093/nar/29.1.308

31. Sim N.L., Kumar P., Hu J., Henikoff S., Schneider G., Ng P.C. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res., 2012, Vol. 40, W1, pp. 452–457. doi: 10.1093/nar/gks539.

32. Steinhaus R., Proft S., Schuelke M., Cooper D.N., Schwarz J.M., Seelow D. MutationTaster2021. Nucleic Acids Res., 2021, Vol. 49, W1, pp. 446–451. doi: 10.1093/nar/gkab266

33. Stenson P.D., Mort M., Ball E.V., Chapman M., Evans K., Azevedo L., Hayden M.J., Heywood S., Millar D.S., Phillips A.D., Cooper D.N. The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting. Hum. Genet., 2020, Vol. 139, no. 10, pp. 1197–1207. doi: 10.1007/s00439-020-02199-3

34. Trivedi R., Nagarajaram H.A. Intrinsically disordered proteins: an overview. Int. J. Mol. Sci., 2022, Vol. 23, no. 22, Article no. 14050. doi: 10.3390/ijms232214050

35. Wu Y. Contact pathway of coagulation and inflammation. Thromb. J., 2015, Vol. 13, Article no. 1, pp. 1–9. doi: 10.1186/s12959-015-0048-y

36. Zanichelli A., Magerl M., Longhurst H., Fabien V., Maurer M. Hereditary angioedema with C1 inhibitor deficiency: delay in diagnosis in Europe. Allergy Asthma Clin. Immunol., 2013, Vol. 9, Article no. 29. doi: 10.1186/1710-1492-9-29