Renal transplantation provides the best long-term treatment for chronic renal failure. Single-nucleotide polymorphisms (SNPs) play a major role in the understanding of the genetic basis of many complex human diseases. Also, the genetics of human phenotype variation could be understood by knowing the functions of these SNPs. It is still a major challenge to identify the functional SNPs in a disease-related gene. This work explored how SNPs mutations in HLA-DRB1 gene could affect renal transplantation rejection. This study was carried out in Ahmed Gasim Hospital, Renal Dialysis Center during the period, from September 2012 to November 2013. Blood samples from five Sudanese patients (different families) with known renal transplantation rejection were collected before hemodialysis, furthermore one blood sample for control. DNA sequences results and detected SNPs were analyzed using bioinformatics tools (BLAST, SIFT, nsSNP Analyzer, PolyPhen, I-mutant, BioEdit, CPH, Chimera, Box shade and Project Hope). In addition, international databases were used for datasets [NCBI, Uniprot]. Results showed that, three SNPs were detected; two of three SNPs were predicted as tolerant or benign (rs1059575, novel) and one was deleterious (rs17885437). This study concluded that the identification of pathological SNPs could be an answer to unknown causes for a lot of organ transplantation rejection cases.
Lysaght, M.J. (2002) Maintenance Dialysis Population Dynamics: Current Trends and Long-Term Implications. Journal of the American Society of Nephrology, 13, 37-40. http://jasn.asnjournals.org/content/13/suppl_1/S37.long
Gilbertson, D.T., Liu, J., Xue, J.L., Louis, T.A., Solid, C.A., Ebben, J.P. and Collins, A.J. (2005) Projecting the Number of Patients with End-Stage Renal Disease in the United States to the Year 2015. Journal of the American Society of Nephrology, 16, 3736-3741. http://jasn.asnjournals.org/content/16/12/3736.long
Elsharif, M.E. and Elsharif, E.G. (2011) Causes of End-Stage Renal Disease in Sudan: A Single-Center Experience. Saudi Journal of Kidney Diseases and Transplantation, 22, 373-376.
Barsoum, R.S. (2006) Chronic Kidney Disease in the Developing World. New England Journal of Medicine, 354, 997- 999. http://www.nejm.org/doi/full/10.1056/NEJMp058318
Hassan, M.M., Dowd, A.A., Mohamed, A.H., Mahalah, S.M.O.S., et al. (2014) Computational Analysis of Deleterious nsSNPs within HLA-DRB1 and HLA-DQB1 Genes Responsible for Allograft Rejection. International Journal of Computational Bioinformatics and In-Silico Modeling, 3, 562-577.
Berno, G., Zaccarelli, M., Goril, C., Tempestilli, M., et al. (2014) Analysis of Single-Nucleotide Polymorphisms (SNPs) in Human CYP3A4 and CYP3A5 Genes: Potential Implications for the Metabolism of HIV Drugs. BMC Medical Genetics, 15, 76. http://www.biomedcentral.com/content/pdf/1471-2350-15-76.pdf
Zhan, X., Dixon, A., Batbayar, N., Bragin, E., et al. (2015) Exonic versus Intronic SNPs: Contrasting Roles in Revealing the Population Genetic Differentiation of a Widespread Bird Species. Heredity (Edinb), 114, 1-9.
Kim, S.K., Park, H.J., Seok, H., Jeon, H.S., et al. (2014) Association Studies of Cytochrome P450, Family 2, Subfamily E, Polypeptide 1 (CYP2E1) Gene Polymorphisms with Acute Rejection in Kidney Transplantation Recipients. Clinical Transplantation, 28, 707-712. http://onlinelibrary.wiley.com/doi/10.1111/ctr.12369/pdf
Ramensky, V., Bork, P. and Sunyaev, S. (2002) Human Nonsynonymous SNPs: Server and Survey. Nucleic Acids Research, 30, 3894-3900. http://nar.oxfordjournals.org/content/30/17/3894.long
Capriotti, E., Fariselli, P., Calabrese and Casadio, R. (2005) Predicting Protein Stability Changes from Sequences Using Support Vector Machines. Bioinformatics, 2, 54-58.
Venselaar, H., Beek, T., Kuipers, R.K., Hekkelma, M.L. and Vriend, G. (2010) Protein Structure Analysis of Mutations Causing Inheritable Diseases. An e-Science Approach with Life Scientist Friendly Interfaces. BMC Bioinformatics, 11, 548. http://www.biomedcentral.com/1471-2105/11/548
Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., et al. (2005) Protein Identification and Analysis Tools on the ExPASy Server. In: Walker, J.M., Ed., The Proteomics Protocols Handbook, Humana Press, 571-607.