Predicting Functional Impacts of Amino Acid Substitutions in Exon 21 of the ATP7B Gene for Wilson Disease Diagnosis

Omar Qahtan Yaseen ^1*, Asra’a Adnan Abdul-Jalil ^2*

This study determined the SAASs' impact on protein function aids in diagnosing genetic diseases like Wilson disease using bioinformatics algorithms.

Abstract

Background: Diagnosing illnesses with overlapping clinical symptoms shows challenges, necessitating precise identification of genetic variations underlying pathogenesis. Here, we focus on Wilson disease, an autosomal recessive disorder characterized by copper accumulation due to mutations in the ATP7B gene. Method: To predict the functional impact of single amino acid substitutions (SAASs) in exon 21 of ATP7B, we employed bioinformatics tools, including SIFT, PolyPhen2, and Provean. Our study, conducted on thirty Iraqi Wilson disease patients, identified missense mutations associated with disease manifestation. Result: Bioinformatics analyses revealed nine potentially deleterious non-synonymous SNPs in exon 21. Functional modifications were predicted more accurately by all programs, indicating their utility in identifying pathogenic variants. Conclusion: Our findings underscore the utility of computational methods in high-throughput SAAS annotation, offering insights for diagnostic screening and therapeutic strategies. Furthermore, our study expands the spectrum of ATP7B mutations implicated in Wilson disease onset, underscoring the role of bioinformatics in elucidating genotype-phenotype correlations and advancing precision medicine.

Keywords: SAASs, ATP7B gene, Wilson disease, Bioinformatics algorithms, Missense mutations.

References

Alirezaie, N., Kernohan, K.D., Hartley, T., Majewski, J. and Hocking, T.D.(2018) ClinPred: prediction tool to identify disease-relevant nonsynonymous singlenucleotide variants. Am. J. Hum. Genet. 103, 474–483.

Al-Mayah, Q. S., Arif, H. S., Shamran, H. A., Abbas, A. A. Q., & Kareem, K. H. (2016). Mutation Profile of Exon 14 and Exon 21 of ATP7B Gene in Patients with Wilson Disease. Medical Journal of Babylon, 13(3), 635-641.‏

Chennen, K., Weber, T., Lornage, X., Kress, A., Bohm, J., Thompson, J., ¨ Laporte, J. et al. (2020) MISTIC: A prediction tool to reveal disease-relevant deleterious missense variants. PLoS One, 15, e0236962.

Gavali, L. V., Mohammed, A. A., Al-Ogaili, M. J., Gaikwad, S. H., Kulkarni, M., Das, R., & Ubale, P. A. (2024). Novel terephthalaldehyde bis (thiosemicarbazone) Schiff base ligand and its transition metal complexes as antibacterial Agents: Synthesis, characterization and biological investigations. Results in Chemistry, 7, 101316.

Gul, B., Firasat, S., Tehreem, R., Shan, T., & Afshan, K. (2022). Analysis of Wilson disease mutations in copper binding domain of ATP7B gene. Plos one, 17(6), e0269833.‏

Hufford, M.B., Seetharam, A.S., Woodhouse, M.R., Chougule, K.M., Ou, S., Liu, J., Ricci, W.A. et al. (2021) De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science, 373, 655–662.

Ioannidis, N.M., Rothstein, J.H., Pejaver, V., Middha, S., McDonnell, S.K., Baheti, S., Musolf, A. et al. (2016) REVEL: an ensemble method for predicting the pathogenicity of rare missense variants. Am. J. Hum. Genet. 99, 877–885.

Kandil, M. A., Aiad, H. A., El-Azab, D. S., El-Goday, S. F., & Tantawy, M. S. (2019). Clinicopathological differentiation between biliary atresia and other causes of neonatal cholestasis. Menoufia Medical Journal, 32(1), 151.‏

Kok, K. F., Hoevenaars, B. M., Waanders, E., & Drenth, J. P. H. (2008). Value of molecular analysis of Wilson's disease in the absence of tissue copper deposits: a novel ATP7B mutation in an adult patient.‏

Kono, T.J.Y., Lei, L., Shih, C.H., Hoffman, P.J., Morrell, P.L. and Fay, J.C.(2018) Comparative genomics approaches accurately predict deleterious variants in plants. G3, 8, 3321–3329.

Kovalev, M.S., Igolkina, A.A., Samsonova, M.G. and Nuzhdin, S.V.(2018) A pipeline for classifying deleterious coding mutations in agricultural plants. Front. Plant Sci. 9, 1734.

Lei, P., Ayton, S., & Bush, A. I. (2021). The essential elements of Alzheimer’s disease. Journal of Biological Chemistry, 296. ‏

Lek, M., Karczewski, K.J., Minikel, E.V., Samocha, K.E., Banks, E., Fennell, T., O’Donnell-Luria, A.H. et al. (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature, 536, 285–291.

Li, B.B., Zhao, Y.X., Liang, L.Y., Ren, H.B., Xing, Y., Chen, L., Sun, M.Z. et al. (2012) Purification and characterization of ZmRIP1, a novel reductantinhibited protein tyrosine phosphatase from maize. Plant Physiol. 159, 671– 681.

Maghool, F., Emami, M. H., Alipour, R., Mohammadzadeh, S., Sereshki, N., Dehkordi, S. A. E., ... & Sahebkar, A. (2023). Rescue effect of curcumin against copper toxicity. Journal of Trace Elements in Medicine and Biology, 127153. ‏

Mohammed, A. A., & Sonawane, K. D. (2022). Destabilizing Alzheimer's Aβ42 protofibrils with oleocanthal: In-silico approach. BIOINFOLET-A Quarterly Journal of Life Sciences, 19(3), 288-295.

Pejaver, V., Urresti, J., Lugo-Martinez, J., Pagel, K.A., Lin, G.N., Nam, H.J., Mort, M. et al. (2020) Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nat. Commun. 11, 5918.

Qahtan, O. (2023). Sorting Intolerant from Tolerant and PolyPhen-2 Algorithms: A Variation in Exon 14 of ATP7B Gene among 4 West Iraqi Families with Wilson’s Disease. Al-Anbar Medical Journal, 19(2), 98-103.‏

Takeda, J.-I., Nanatsue, K., Yamagishi, R., Ito, M., Haga, N., Hirata, H., Ogi, T. et al. (2020) InMeRF: prediction of pathogenicity of missense variants by individual modeling for each amino acid substitution. NAR Genom. Bioinform. 2, lqaa038.

Tao, Y.F., Luo, H., Xu, J.B., Cruickshank, A., Zhao, X.R., Teng, F., Hathorn, A. et al. (2021) Extensive variation within the pan-genome of cultivated and wild sorghum. Nat. Plants, 7, 766–773.

Tasmeen, R., Karim, A. B., Banu, L. A., Hossain, E., Rokunuzzaman, M., Majumder, W., ... & Hasan, M. S. (2022). Mutational analysis of exon 8 and exon 14 of ATP7B gene in Bangladeshi children with Wilson disease. Indian Journal of Gastroenterology, 41(5), 456-464. ‏

Verkade, H. J., Bezerra, J. A., Davenport, M., Schreiber, R. A., Mieli-Vergani, G., Hulscher, J. B., ... & Petersen, C. (2016). Biliary atresia and other cholestatic childhood diseases: advances and future challenges. Journal of hepatology, 65(3), 631-642.‏

Wang, M.J., Zhao, X.M., Takemoto, K., Xu, H.S., Li, Y., Akutsu, T. and Song, J.N.(2012) FunSAV: predicting the functional effect of single amino acid variants using a two-stage random forest model. PLoS One, 7, e43847.

Wang, X.P., Chen, L.M., Liu, W.X., Shen, L.K., Wang, F.L., Zhou, Y., Zhang, Z.D. et al. (2016) AtKC1 and CIPK23 synergistically modulate AKT1-mediated lowpotassium stress responses in Arabidopsis. Plant Physiol. 170, 2264–2277.

Xiong, D., Lee, D., Li, L., Zhao, Q., & Yu, H. (2022). Implications of disease-related mutations at protein–protein interfaces. Current opinion in structural biology, 72, 219-225. ‏

Xu, D., Shao, Q., Zhou, C., Mahmood, A., & Zhang, J. (2023). In silico analysis of nsSNPs of human KRAS gene and protein modeling using bioinformatic tools. ACS omega, 8(14), 13362-13370.‏

Xu, R., Duan, P.G., Yu, H.Y., Zhou, Z.K., Zhang, B.L., Wang, R.C., Li, J. et al. (2018) Control of grain size and weight by the OsMKKK10-OsMKK4- OsMAPK6 signaling pathway in Rice. Mol. Plant. 11, 860–873.

Yaseen, O. Q., Al-Ani, M. Q., & Majeed, Y. H. (2020). In-Silico prediction of impact on protein function caused by non-synonymous single nucleotide polymorphism in human ATP7B gene associated with Wilson disease. Research Journal of Biotechnology Vol, 15, 3. ‏

Zhao, Q., Feng, Q., Lu, H.Y., Li, Y., Wang, A.H., Tian, Q.L., Zhan, Q.L. et al. (2018) Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice. Nat. Genet. 50, 278–284.