Investigation of Relationship Between Small Noncoding RNA (sncRNA) Expression Levels and Serum Iron, Copper, and Zinc Levels in Clinical Diagnosed Multiple Sclerosis Patients.
Arzu AyNevra AlkanliEngin AtliHakan GurkanTevfik GulyasarSibel GulerTammam SipahiNecdet SutPublished in: Molecular neurobiology (2022)
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.
Keyphrases
- multiple sclerosis
- end stage renal disease
- newly diagnosed
- ejection fraction
- mass spectrometry
- peritoneal dialysis
- ms ms
- type diabetes
- insulin resistance
- poor prognosis
- oxidative stress
- cell proliferation
- machine learning
- long non coding rna
- metabolic syndrome
- mild cognitive impairment
- high fat diet
- skeletal muscle
- big data
- patient reported outcomes
- electronic health record
- case report
- highly efficient