Abstract
In our study, we aimed to investigate the relationship between microRNA (miRNA) expression levels and serum iron (Fe), copper (Cu), and zinc (Zn) levels in Multiple sclerosis (MS) patients. Total RNA was isolated from peripheral venous blood containing ethylenediaminetetraacetic acid (EDTA) of MS patients and controls. Total RNA was labeled with Cy3-CTP fluorescent dye. Hybridization of samples was performed on microarray slides and arrays were scanned. Data argument and bioinformatics analysis were performed. Atomic absorption spectrophotometer method was used to measure serum Fe, Cu, and Zn levels. In our study, in bioinformatics analysis, although differently expressed miRNAs were not detected between 16 MS patients and 16 controls, hsa-miR-744-5p upregulation was detected between 4 MS patients and 4 controls. This may be stem from the patient group consisting of MS patients who have never had an attack for 1 year. Serum iron levels were detected significantly higher in the 16 MS patients compared to the 16 controls. This may be stem from the increase in iron accumulation based on inflammation in MS disease. According to the findings in our study, hsa-miR-744-5p upregulation has been determined as an early diagnostic biomarker for the development together of insulin resistance, diabetes mellitus associated with insulin signaling, and Alzheimer’s diseases. Therefore, hsa-miR-744-5p is recommended as an important biomarker for the development together of diabetes mellitus, Alzheimer’s disease, and MS disease. In addition, increased serum Fe levels may be suggested as an important biomarker for neurodegenerative diseases such as Parkinson’s disease, Alzheimer’s disease, and MS disease.
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Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.
References
Angerstein C, Hecker M, Paap BK, Koczan D, Thamilarasan M, Thiesen HJ et al (2012) Integration of MicroRNA databases to study MicroRNAs associated with multiple sclerosis. Mol Neurobiol 45(3):520–535. https://doi.org/10.1007/s12035-012-8270-0
Hecker M, Fitzner B, Jäger K, Bühring J, Schwartz M, Hartmann A et al (2021) Leukocyte telomere length in patients with multiple sclerosis and its association with clinical phenotypes. Mol Neurobiol 58(6):2886–2896. https://doi.org/10.1007/s12035-021-02315-y
Nowak A, Wicik Z, Wolska M, Shahzadi A, Szwed P, Jarosz-Popek J et al (2022) The role of non-coding RNAs in neuroinflammatory process in multiple sclerosis. Mol Neurobiol 59(8):4651–4668. https://doi.org/10.1007/s12035-022-02854-y
Liu M, Hou X, Zhang P, Hao Y, Yang Y, Wu X et al (2013) Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis. Mol Biol Rep 40(5):3731–3737
Keller A, Leidinger P, Lange J, Borries A, Schroers H, Scheffler M et al (2009) Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. PLoS ONE 4(10):e7440
Piket E, Zheleznyakova GY, Kular L, Jagodic M (2019) Small non-coding RNAs as important players, biomarkers and therapeutic T targets in multiple sclerosis: a comprehensive overview. J Autoimmun 101:17–25
Pilson Q, Smith S, Jefferies CA, Gabhann-Dromgoole JN, Murphy CC (2020) miR-744-5p contributes to ocular inflammation in patients with primary Sjogrens Syndrome. Sci Rep 10:7484. https://doi.org/10.1038/s41598-020-64422-5
Keller A, Leidinger P, Meese E, Haas J, Backes C, Rasche L et al (2015) Next-generation sequencing identifies altered whole blood microRNAs in neuromyelitis optica spectrum disorder which may permit discrimination from multiple sclerosis. J Neuroinflammation 12:196
Chen C, Zhou Y, Wang J, Yan Y, Peng L, Qiu W (2018) Dysregulated microRNA involvement in multiple sclerosis by induction of T helper 17 cell differentiation. Front Immunol 9:1256
Janghorbani M, Shaygannejad V, Hakimdavood M, Salari M (2017) Trace elements in serum samples of patients with multiple sclerosis. Athens Journal of Health 4(2):145–154
Tamburo E, Varrica D, Dongarrà G, Grimaldi LM (2015) Trace elements in scalp hair samples from patients with relapsing-remitting multiple sclerosis. PLoS ONE 10(4):e0122142
Xu Z, Shi Z, Li Y (2014) The crosstalk between micro RNA and iron homeostasis. Int J Genomic Med 1:112
Bredholt M, Frederiksen JL (2016) Zinc in multiple sclerosis: a systematic review and meta-analysis. ASN Neuro 8(3):1759091416651511
Rink L, Gabriel P (2000) Zinc and the immune system. Proc Nutr Soc 59(4):541–552
Socha K, Karpinska E, Kochanowicz J (2017) Dietary habits; concentration of copper, zinc, and Cu-to-Zn ratio in serum and ability status of patients with relapsing-remitting multiple sclerosis. Nutrition 39–40:76–81
Ryu MS, Langkamp-Henken B, Chang SM, Shankar MN, Cousins RJ (2011) Genomic analysis, cytokine expression, and microRNA profiling reveal biomarkers of human dietary zinc depletion and homeostasis. Proc Natl Acad Sci U S A 108(52):20970–20975
Smith DK, Feldman EB, Feldman DS (1989) The trace elements status in multiple sclerosis. Am J Clin Nutr 50(1):136–140
Pilon M (2017) The copper microRNAs. New Phytol 213(3):1030–1035
Baulina NM, Kulakova OG, Favorova OO (2016) MicroRNAs: the role in autoimmune inflammation. Acta Naturae 8(1):21–33
Gregory SG, Schmidt S, Seth P, Oksenberg JR, Hart J, Prokop A et al (2007) Multiple sclerosis genetics group Interleukin 7 receptor alpha chain (IL7R) shows allelic and functional association with multiple sclerosis. Nat Genet 39(9):1083–91
Sanna A, Firinu D, Zavattari P, Valera P (2018) Zinc status and autoimmunity: a systematic review and meta-analysis. Nutrients 10(1):68
QIAamp RNA Blood Mini Handbook, 3. Kit Contents. QIAamp RNA Blood Mini Kit. Catalog no. Preparations per Kit. 52304. 50. QIAamp Spin Columns (clear). 2021; file:///Users/nevraalkanli/Downloads/HB 0322–004_HB_QA_RNA_Blood_Mini_0221_WW%20(3).pdf
Schroeder A, Mueller O, Stocker S, Salowsky R, Leiber M, Gassmann M et al (2006) The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Mol Biol 7:3
miRNA microarray system with miRNA complete labeling and Hyb kit protocol. Agilent Technologies. 2021. www.agilent.com. Accessed Oct 2021
Agilent feature extraction software, automated image analysis paired with QC tools product note. Agilent Technologies. 2016. www.agilent.com. Accessed Jan 2016
Ay A, Gulyasar T, Alkanli N, Sipahi T, Cicin I, Kocak Z et al (2021) Investigation of the relationship between GSTM1 gene variations and serum trace elements, plasma malondialdehyde levels in patients with colorectal cancer. Mol Biol Rep 48(10):6911–6921
Martinez B, Peplow PV (2020) MicroRNAs in blood and cerebrospinal fluid as diagnostic biomarkers of multiple sclerosis and to monitor disease progression. Neural Regen Res 15(4):606–619
Keller A, Leidinger P, Bauer A, Elsharawy A, Haas J, Backes C et al (2011) Toward the blood-borne miRNome of human diseases. Nat Methods 8(10):841–843
Otaegui D, Baranzini SE, Armañanzas R, Calvo B, Muñoz-Culla M, Khankhanian P et al (2009) Differential micro RNA expression in PBMC from multiple sclerosis patients. PLoS ONE 4(7):e6309
Cox MB, Cairns MJ, Gandhi KS, Carroll AP, Moscovis S, Stewart GJ et al (2010) MicroRNAs miR-17 and miR-20a inhibit T cell activation genes and are under-expressed in MS whole blood. PLoS ONE 5(8):e12132. https://doi.org/10.1371/journal.pone.0012132
Junker A, Hohlfeld R, Meinl E (2011) The emerging role of microRNAs in multiple sclerosis. Nat Rev Neurol 7(1):56–59
Ghiam S, Eslahchi C, Shahpasand K, Habibi-Rezaei M, Gharaghani S (2020) Exploring the role of non-coding RNAs as potential candidate biomarkers in the cross-talk between diabetes mellitus and Alzheimer’s disease. Front Aging Neurosci 14:955461. https://doi.org/10.3389/fnagi.2022.955461
Kabir MT, Uddin MS, Zaman S, Begum Y, Ashraf GM, Bin-Jumah MN et al (2021) Molecular mechanisms of metal toxicity in the pathogenesis of Alzheimer’s disease. Mol Neurobiol 58(1):1–20. https://doi.org/10.1007/s12035-020-02096-w
Bjørklund G, Dadar M, Chirumbolo S, Aaseth J (2020) The role of xenobiotics and trace metals in Parkinson’s disease. Mol Neurobiol 57(3):1405–1417. https://doi.org/10.1007/s12035-019-01832-1
Al-Zubaidi MA (2012) The effect of interferon Beta-1b and methylprednisolone treatment on the serum trace elements in Iraqi patients with multiple sclerosis. J Clin Diagn Res 6(6):994–998
Oraby MI, Hussein M, Abd Elkareem R, Eman E (2019) The emerging role of serum zinc in motor disability and radiological findings in patients with multiple sclerosis. Egypt J Neurol Psychiatry Neurosurg 55:60
Tapiero H, Townsend DM, Tew KD (2003) Trace elements in human physiology and pathology. Copper Biomed Pharmacother 57(9):386–398
Pawlitzki M, Uebelhör J, Sweeney-Reed CM (2018) Lower serum zinc levels in patients with multiple sclerosis compared to healthy controls. Nutrients 10(8):967
Acknowledgements
Our study was carried out in the Department of Biophysics, Department of Medical Genetics, and Department of Neurology at Trakya University.
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This study was supported by the Coordinatorship of Scientific Research Projects of Trakya University with 2017/68 project number.
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AA and NA designed the experiments. AA, NA, EA, HG, TG, and TS performed the experiments. AA, NA, EA, and HG analyzed the data. Samples collection was performed by AA and SG. Statistical analyses were performed by NS. AA and NA wrote the paper. All authors read and approved the final manuscript. The corresponding author attests that all listed authors meet the authorship criteria and that no other authors meeting the criteria have been omitted.
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The approval of the ethics committee was obtained from the Trakya University Faculty of Medicine Non-Invasive Ethics Committee (Protocol code: TÜTF-BAEK 2017/11).
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Signed informed consent forms were collected from each of the MS patients and healthy controls.
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The author, Arzu Ay, Nevra Alkanli, Engin Atli, Hakan Gurkan, Tevfik Gulyasar, Sibel Guler, Tammam Sipahi, Necdet Sut have read and approved the final manuscript for submission. We confirm the tables and figures are original for this article.
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Ay, A., Alkanli, N., Atli, E. et al. Investigation of Relationship Between Small Noncoding RNA (sncRNA) Expression Levels and Serum Iron, Copper, and Zinc Levels in Clinical Diagnosed Multiple Sclerosis Patients. Mol Neurobiol 60, 875–883 (2023). https://doi.org/10.1007/s12035-022-03135-4
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DOI: https://doi.org/10.1007/s12035-022-03135-4