Abstract
Multiple Sclerosis (MS) is an autoimmune disease that severely impacts the central nervous system. Thanks to the evolutionary genetic information studied and published, researches have started to study MS from a genetic perspective. This paper provides a study of six single-nucleotide polymorphisms (SNPs)—MIR137HG (rs1625579), GAS5 (rs2067079), MIR3142HG (rs57095329), MIR146A (rs2910164), MIR155HG (rs767649) and IRAK1 (rs3027898)—and demonstrates their association with MS. This study was applied over an Egyptian dataset of 38 MS patients and 35 controls. Hence, different models were applied, Dominant, Recessive and Genotypic models along with Fisher’s Exact method, Basic case–control analysis and Logistic regression analysis. This paper shows that the SNPs rs1625579, rs57095329, rs767649 and rs3027898 are associated with MS (p value < 0.05) according to all tested models except for Recessive model, that has add-in the relevance of rs1625579, rs57095329, rs2910164 and rs767649 with MS disease.
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References
Ali MA et al (2020) Relationship between miR-155 and miR-146a polymorphisms and susceptibility to multiple sclerosis in an Egyptian cohort. Biomed Rep 12(5):276–284
Chen J et al (2016) A pilot study on commonality and specificity of copy number variants in schizophrenia and bipolar disorder. Transl Psychiatry 6(5):e824–e824
Clarke GM, Anderson CA, Pettersson FH, Cardon LR, Morris AP, Zondervan KT (2011) Basic statistical analysis in genetic case-control studies. Nat Protoc 6(2):121–133
Egger C et al (2017) MRI FLAIR lesion segmentation in multiple sclerosis: does automated segmentation hold up with manual annotation? NeuroImage Clin. 13:264–270
Abd El Hamid et al (2019) Developing an early predictive system for identifying genetic biomarkers associated to Alzheimer's disease using machine learning techniques. Biomed Eng Appl Basis Commun 31(5):1950040
Farias FR, Klein PC, Soder RB, Becker J, Pinho MS (2016) MRI interpolation for multiple sclerosis lesion quantification. In: Proceedings - international computer software and applications conference, 2016
Hecker M et al (2019) A genetic variant associated with multiple sclerosis inversely affects the expression of CD58 and microRNA-548ac from the same gene. PLoS Genet 15(2):e1007961
Hussain R et al (2013) The neural androgen receptor: a therapeutic target for myelin repair in chronic demyelination. Brain 136(1):132–146
Koch CA, Robyn JA, Pacak K (1999) How do levels of (endogenous) glucocorticoids, interleukin-10 and interleukin-12 relate to multiple sclerosis relapse before, during and after pregnancy? Clin Endocrinol (Oxf) 50(6):818–819
Koch CA, Krabbe S, Hehmke B (2018) Statins, metformin, proprotein-convertase-subtilisin-kexin type-9 (PCSK9) inhibitors and sex hormones: Immunomodulatory properties? Rev Endocr Metab Disord 19(4):363–395
Labib DA, Shaker OG, El Refai RM, Ghoniem SA, Elmazny A (2019) Association between miRNA-146a and polymorphisms of its target gene, IRAK1, regarding susceptibility to and clinical features of systemic lupus erythematous and multiple sclerosis. Lab Med 50(1):34–41
Mostafa et al (2016) Identifying genetic biomarkers associated to Alzheimer ’s disease using support vector machine. In: 2016 8th CIBEC. IEEE, pp 5–9
Li K et al (2015) Genetic association of MiR-146a with multiple sclerosis susceptibility in the Chinese population. Cell Physiol Biochem 35:281–291
Paramonova N et al (2020) An intergenic rs9275596 polymorphism on Chr. 6p21 Is associated with multiple sclerosis in latvians. Medicina 56:4
Park R, Lee WJ, Ji JD (2016) Association between the three functional miR-146a single-nucleotide polymorphisms, rs2910164, rs57095329, and rs2431697, and autoimmune disease susceptibility: a meta-analysis. Autoimmunity 49(7):451–458
Purcell S (2010) PLINK (1.07) Documentation
Qu HQ, Tien M, Polychronakos C (2010) Statistical significance in genetic association studies. Clin Investig Med 33(5):E266
Ripke S, Sanders AR, Kendler KS, Levinson DF (GWAS) Consortium et al. (2011) Genome-wide association study identifies five new schizophrenia loci. Nat Genet 43(10):969–976
Wang L, Jia P, Wolfinger RD, Chen X, Zhao Z (2011) Gene set analysis of genome-wide association studies: methodological issues and perspectives. Genomics 98(1):1–11
Wienbrandt L, Kässens JC, Hübenthal M, Ellinghaus D (2018) 1,000x faster than PLINK: genome-wide epistasis detection with logistic regression using combined FPGA and GPU accelerators. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Zager A (2020) Modulating the immune response with the wake-promoting drug modafinil: a potential therapeutic approach for inflammatory disorders. Brain Behav Immun
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Hamid, M.M.A.E., Ali, N.M., Saad, M.N. et al. Multiple sclerosis: an associated single-nucleotide polymorphism study on Egyptian population. Netw Model Anal Health Inform Bioinforma 9, 48 (2020). https://doi.org/10.1007/s13721-020-00255-6
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DOI: https://doi.org/10.1007/s13721-020-00255-6