20.500.12556/RUL-137511 Suicide and changes in expression of neuronal miRNA predicted by an algorithm search through miRNA databases Suicide is multifactorial and polygenic phenotype, affected by environmental and genetic factors. Among epigenetic mechanisms, miRNAs have been studied, but so far no very concise results exist. To overcome limitations of candidate miRNA and whole genome sequencing approaches, we created an in silico analysis algorithm that would help select the best suitable miRNAs that target the most interesting genes associated with suicidality. We used databases/web algorithms DIANA microT, miRDB, miRmap, miRWalk, and TargetScan and candidate genes SLC6A4, HTR1A, BDNF, NR3C1, ZNF714, and NRIP3. Based on a prediction algorithm, we have chosen miRNAs that are targeting regulation of the genes listed, and are at the same time being expressed in the brain. The highest ranking scores were obtained for hsa-miR-4516, hsa-miR-3135b, hsa-miR-124-3p, hsa-miR-129-5p, hsa-miR-27b-3p, hsa-miR-381-3p, hsa-miR-4286. Expression of these miRNAs was tested in the brain tissue of 40 suicide completers and controls, and hsa-miR-4516 and hsa-miR-381-3p showed a trend for statistical significance. We also checked the expression of the target genes of these miRNAs, and for NR3C1 expression was lower in suicide completers compared to controls, which is in accordance with the available literature results. To determine the miRNAs that are most suitable for further suicidality research, more studies, combining in silico analysis and wet lab experiments, should be performed. psychiatry epigenetics suicidal behaviour Brodmann area 10 non-coding RNA micro RNA psihiatrija epigenetika samomorilno vedenje true false true Angleški jezik Slovenski jezik Članek v reviji 2022-06-20 09:52:45 2022-06-20 09:52:52 2022-09-15 04:15:18 0000-00-00 00:00:00 2022 0 0 13 str. iss. 4, art. 562 Vol. 13 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 616.89 2073-4425 10.3390/genes13040562 102437123 RAZ_Videtic_Paska_Alja_2022.pdf RAZ_Videtic_Paska_Alja_2022.pdf 1 30ABEEE8306669D6E06B790DDD708374 a2cae1a560a46c7ac926df766f91cad95fc73006880c131511d26b54b07e612e cd64b8f6-f06d-11ec-8aca-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=157476 https://www.mdpi.com/2073-4425/13/4/562 0 f057a45b-f06d-11ec-8aca-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=157477 Medicinska fakulteta 0 0 0