Evaluation of Genes and Molecular Pathways Involved in Pathogenesis of Sickle Cell Anemia: A Bioinformatics Analysis and Future Perspective
-
Reza Maddah
,
Sareh Etemad
,
Bahareh Shateri Amiri
,
Hajarossadat Ghaderi
,
Hamidreza Zarei
,
Ferdos Faghihkhorasani
,
Hadi Rezaeeyan
Abstract
Background: Sickle cell disease (SCD) is one of the hematological disorders characterized by a defect in the structure and function of globin chains. Hereditary factors play an important role in the pathogenesis of SCD. We aimed to investigate the genes and pathways related to the pathogenesis of SCD.
Methods: Microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. LIMMA package of R-software was used to detect UP and Down regulations between SCD and control subjects. Enrichment analysis and Protein-protein interaction (PPI) networks were performed using GeneCodis4 software and GeneMANIA database, respectively. PrognoScan database was used to evaluate the relationship between the hub genes and patients' survival.
Results: Overall, 447 DEGs were identified in SCD patients compared to control subjects. Out of 447 DEGs, 345 genes were up-regulated and 102 genes were down-regulated. Effective hub genes in SCD pathogenesis include SLC4A1, DTL, EPB42, SNCA, and TOP2A. In addition, hub genes had a high diagnostic value.
Conclusion: Evaluation of hub genes in SCD can be used as a diagnostic panel to detect high-risk patients. In addition, by identifying the UP and Down stream pathways, treatment strategies in the monitoring and treatment of patients can be designed.
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23. Bahadoram S, Keikhaei B, Bahadoram M, et al (2021). Renal complications of sickle cell disease. J Renal Endocrinol, 7:e20.
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25. Subarna C, Thomas NW (2015). Sickle cell disease: a neglected chronic disease of increasing global health importance. Arch Dis Child, 100 (1):48-53.
26. Albadine R, Wang W, Brownlee NA, et al (2009). Topoisomerase II α Status in Renal Medullary Carcinoma: Immuno-Expression and Gene Copy Alterations of a Potential Target of Therapy. J Urol, 182 (2):735-740.
27. Bhaskar LV (2019). Factor V Leiden and prothrombin G20210A mutations and risk of vaso-occlusive complications in sickle cell disease: A meta-analysis through the lens of nephrology. J Nephropharmacol, 8 (2):e16.
28. Hahn CK, Lowrey CH (2014). Induction of fetal hemoglobin through enhanced translation efficiency of γ-globin mRNA. Blood, 124 (17):2730-2734.
29. Huang Z, Du G, Huang X, et al (2018). The enhancer RNA lnc-SLC4A1-1 epigenetically regulates unexplained recurrent pregnancy loss (URPL) by activating CXCL8 and NF-kB pathway. EBioMedicine, 38:162-170.
30. Miller R, Coyne E, Crowgey EL, et al (2020). Implementation of a learning healthcare system for sickle cell disease. JAMIA Open, 3 (3):349-359.
31. Li Z, Wang R, Qiu C, et al (2022). Role of DTL in Hepatocellular Carcinoma and Its Impact on the Tumor Microenvironment. Front Immunol, 13:834606.
32. McGann PT, Hernandez AG, Ware RE (2017). Sickle cell anemia in sub-Saharan Africa: advancing the clinical paradigm through partnerships and research. Blood, 129 (2):155-161.
33. Wang H, Zhang J (2022). Identification of DTL as Related Biomarker and Immune Infiltration Characteristics of Nasopharyngeal Carcinoma via Comprehensive Strategies. Int J Gen Med, 15:2329-2345.
34. Fan Q, Lu Q, Wang G, et al (2022). Optimizing component formula suppresses lung cancer by blocking DTL-mediated PDCD4 ubiquitination to regulate the MAPK/JNK pathway. J Ethnopharmacol, 299:115546.
35. Piel FB, Steinberg MH, Rees DC (2017). Sickle Cell Disease. N Engl J Med, 376 (16):1561-1573.
36. Zhao E, Xie H, Zhang Y (2021). Identification of Differentially Expressed Genes Associated with Idiopathic Pulmonary Arterial Hypertension by Integrated Bioinformatics Approaches. J Comput Biol, 28 (1):79-88.
37. Chen M, Dun Y, Zhang W, Liu S (2022). Identification of differentially expressed genes associated with coronary in-stent restenosis by integrated bioinformatics approaches. Ann Palliat Med, 11 (6):1940-1953.
2. Rees DC, Williams TN, Gladwin MT (2010). Sickle-cell disease. Lancet, 376 (9757):2018-2031.
3. Piel FB, Patil AP, Howes RE, et al (2013). Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates. Lancet, 381 (9861):142-151.
4. Tisdale JF, Thein SL, Eaton WA (2020). Treating sickle cell anemia. Science, 367 (6483):1198-1199.
5. Wonkam A, Mnika K, Ngo Bitoungui VJ, et al (2018). Clinical and genetic factors are associated with pain and hospitalisation rates in sickle cell anaemia in Cameroon. Br J Haematol, 180 (1):134-146.
6. Torres LS, Asada N, Weiss MJ, et al (2022). Recent advances in “sickle and niche” research - Tribute to Dr. Paul S Frenette. Stem Cell Reports, 17 (7):1509-1535.
7. Sheikh M, Ostadrahimi P, Salarzaei M, et al (2021). Cardiac Complications in Pregnancy: A Systematic Review and Meta-Analysis of Diagnostic Accuracy of BNP and N-Terminal Pro-BNP. Cardiol Ther, 10 (2):501-514.
8. Chang AK, Ginter Summarell CC, Birdie PT, et al (2018). Genetic modifiers of severity in sickle cell disease. Clin Hemorheol Microcirc, 68(2-3):147-164.
9. Bhaskar L, Pattnaik S (2023). IL1RN VNTR Polymorphism and kidney damage in sickle cell anemia patients. J Nephropharmacol, 12 (1):e10437.
10. Pinto VM, Balocco M, Quintino S, Forni GL (2019). Sickle cell disease: a review for the internist. Intern Emerg Med, 14:1051-1064.
11. Hounkpe BW, Fiusa MML, Colella MP, et al (2015). Role of innate immunity-triggered pathways in the pathogenesis of Sickle Cell Disease: a meta-analysis of gene expression studies. Sci Rep, 5 : 17822.
12. Toudeshkchouei MG, Tavakoli A, Mohammadghasemi H, et al (2022). Recent approaches to mRNA vaccine delivery by lipid-based vectors prepared by continuous-flow microfluidic devices. Future Med Chem, 14 (21):1561-1581.
13. Draghici S, Khatri P, Tarca AL, et al (2007). A systems biology approach for pathway level analysis. Genome Res, 17 (10):1537-1545.
14. Gupta A, Gupta S, Mani R, et al (2021). Expression of Human epidermal growth factor receptor 2, Survivin, Enhancer of zeste homolog -2, Cyclooxygenase-2, p53 and p16 molecular markers in Gall bladder carcinoma. J Carcinog, 20:7.
15. Ward CM, Li B, Pace BS (2016). Stable expression of miR-34a mediates fetal hemoglobin induction in K562 cells. Exp Biol Med (Maywood), 241 (7):719-729.
16. Miccio A, Blobel GA (2010). Role of the GATA-1/FOG-1/NuRD Pathway in the Expression of Human β-Like Globin Genes. Mol Cell Biol, 30 (14):3460-3470.
17. Lee YT, de Vasconcellos JF, Byrnes C, et al (2015). Erythroid-Specific Expression of LIN28A Is Sufficient for Robust Gamma-Globin Gene and Protein Expression in Adult Erythroblasts. PLoS One, 10 (12):e0144977.
18. Zhao W, Kitidis C, Fleming MD, et al (2006). Erythropoietin stimulates phosphorylation and activation of GATA-1 via the PI3-kinase/AKT signaling pathway. Blood, 107 (3):907-915.
19. Lugus JJ, Park C, Ma YD, Choi K (2009). Both primitive and definitive blood cells are derived from Flk-1+ mesoderm. Blood, 113 (3):563-566.
20. Piel FB, Hay SI, Gupta S, et al (2013). Global Burden of Sickle Cell Anaemia in Children under Five, 2010–2050: Modelling Based on Demographics, Excess Mortality, and Interventions. PLoS Med, 10 (7):e1001484.
21. Peng L, Liu J-Q, Xu C, et al (2019). The prolonged interval between induction chemotherapy and radiotherapy is associated with poor prognosis in patients with nasopharyngeal carcinoma. Radiat Oncol, 14 (1):9.
22. Podar K, Anderson KC (2010). A therapeutic role for targeting c-Myc/Hif-1- dependent signaling pathways. Cell Cycle, 9 (9):1722-1728.
23. Bahadoram S, Keikhaei B, Bahadoram M, et al (2021). Renal complications of sickle cell disease. J Renal Endocrinol, 7:e20.
24. Sheikh M, Tajdini M, Shafiee A, et al (2017). Association of serum gamma-glutamyltransferase and premature coronary artery disease. Neth Heart J, 25 (7-8):439-445.
25. Subarna C, Thomas NW (2015). Sickle cell disease: a neglected chronic disease of increasing global health importance. Arch Dis Child, 100 (1):48-53.
26. Albadine R, Wang W, Brownlee NA, et al (2009). Topoisomerase II α Status in Renal Medullary Carcinoma: Immuno-Expression and Gene Copy Alterations of a Potential Target of Therapy. J Urol, 182 (2):735-740.
27. Bhaskar LV (2019). Factor V Leiden and prothrombin G20210A mutations and risk of vaso-occlusive complications in sickle cell disease: A meta-analysis through the lens of nephrology. J Nephropharmacol, 8 (2):e16.
28. Hahn CK, Lowrey CH (2014). Induction of fetal hemoglobin through enhanced translation efficiency of γ-globin mRNA. Blood, 124 (17):2730-2734.
29. Huang Z, Du G, Huang X, et al (2018). The enhancer RNA lnc-SLC4A1-1 epigenetically regulates unexplained recurrent pregnancy loss (URPL) by activating CXCL8 and NF-kB pathway. EBioMedicine, 38:162-170.
30. Miller R, Coyne E, Crowgey EL, et al (2020). Implementation of a learning healthcare system for sickle cell disease. JAMIA Open, 3 (3):349-359.
31. Li Z, Wang R, Qiu C, et al (2022). Role of DTL in Hepatocellular Carcinoma and Its Impact on the Tumor Microenvironment. Front Immunol, 13:834606.
32. McGann PT, Hernandez AG, Ware RE (2017). Sickle cell anemia in sub-Saharan Africa: advancing the clinical paradigm through partnerships and research. Blood, 129 (2):155-161.
33. Wang H, Zhang J (2022). Identification of DTL as Related Biomarker and Immune Infiltration Characteristics of Nasopharyngeal Carcinoma via Comprehensive Strategies. Int J Gen Med, 15:2329-2345.
34. Fan Q, Lu Q, Wang G, et al (2022). Optimizing component formula suppresses lung cancer by blocking DTL-mediated PDCD4 ubiquitination to regulate the MAPK/JNK pathway. J Ethnopharmacol, 299:115546.
35. Piel FB, Steinberg MH, Rees DC (2017). Sickle Cell Disease. N Engl J Med, 376 (16):1561-1573.
36. Zhao E, Xie H, Zhang Y (2021). Identification of Differentially Expressed Genes Associated with Idiopathic Pulmonary Arterial Hypertension by Integrated Bioinformatics Approaches. J Comput Biol, 28 (1):79-88.
37. Chen M, Dun Y, Zhang W, Liu S (2022). Identification of differentially expressed genes associated with coronary in-stent restenosis by integrated bioinformatics approaches. Ann Palliat Med, 11 (6):1940-1953.
| Files | ||
| Issue | Vol 53 No 6 (2024) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v53i6.15914 | |
| Keywords | ||
| Sickle cell Gene Molecular pathway Pathogenesis | ||
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How to Cite
1.
Maddah R, Etemad S, Shateri Amiri B, Ghaderi H, Zarei H, Faghihkhorasani F, Rezaeeyan H. Evaluation of Genes and Molecular Pathways Involved in Pathogenesis of Sickle Cell Anemia: A Bioinformatics Analysis and Future Perspective. Iran J Public Health. 2024;53(6):1404-1415.
