Submitted:
02 May 2025
Posted:
06 May 2025
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Results
2.1. Univariate and Multivariate Comparisons
2.2. Optimal miRNA Thresholds and Correlations with Other Analyzed Variables
3. Discussion
Limitations
4. Materials and Methods
Neuropsychiatric Assessment
Anesthesia
Surgery
Laboratory Measurements
Exosome Isolation
Isolation and Purification of miRNA
Expression Profile of miRNA Genes
cDNA Synthesis and Digital Quantitative PCR
Statistical Analysis
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
| Cycling step | Temperature, °C | Time | Ramp rate | No of cycles | |
| miR_96-5p | Enzyme activation | 95 | 10 min | 1°C/sec | 1 |
| Enzyme activation | 94 | 30 sec | 50 | ||
| Annealing/extension | 62.5 | 1 min | 50 | ||
| Enzyme deactivation | 98 | 10 min | 1 | ||
| Hold | 4 | Infinite | 1 | ||
| miR_34c-5p | Enzyme activation | 95 | 10 min | 2.5°C/sec | 1 |
| Denaturation | 94 | 30 sec | 40 | ||
| Annealing/extension | 60 | 1 min | 40 | ||
| Enzyme deactivation | 98 | 10 min | 1 | ||
| Hold | 4 | Infinite | 1 | ||
| miR_9-3p | Enzyme activation | 95 | 10 min | 1°C/sec | 1 |
| Denaturation | 94 | 30 sec | 50 | ||
| Annealing/extension | 62.5 | 1 min | 50 | ||
| Enzyme deactivation | 98 | 10 min | 1 | ||
| Hold | 4 | Infinite | 1 | ||
| miR_183-5p | Enzyme activation | 95 | 10 min | 1°C/sec | 1 |
| Denaturation | 94 | 30 sec | 50 | ||
| Annealing/extension | 62 | 1 min | 50 | ||
| Enzyme deactivation | 98 | 10 min | 1 | ||
| Hold | 4 | Infinite | 1 | ||
| miR_374-3p | Enzyme activation | 95 | 10 min | 2.5°C/sec | 1 |
| Denaturation | 94 | 30 sec | 40 | ||
| Annealing/extension | 60 | 1 min | 40 | ||
| Enzyme deactivation | 98 | 10 min | 1 | ||
| Hold | 4 | Infinite | 1 |
References
- Al Farsi RS, Al Alawi AM, Al Huraizi AR, Al-Saadi T, Al-Hamadani N, Al Zeedy K, et al. (2023): Delirium in Medically Hospitalized Patients: Prevalence, Recognition and Risk Factors: A Prospective Cohort Study. J Clin Med 7;12(12):3897. [CrossRef]
- Kaźmierski J, Miler P, Pawlak A, Jerczyńska H, Nowakowska K, Walkiewicz G, et al. (2022): Increased postoperative myeloperoxidase concentration associated with low baseline antioxidant capacity as the risk factor of delirium after cardiac surgery. Ann Med. 54(1):610-616. [CrossRef]
- Vasilevskis EE, Han JH, Hughes CG, Ely EW (2012): Epidemiology and risk factors for delirium across hospital settings. Best Pract Res Clin Anaesthesiol. 26(3):277-87. [CrossRef]
- Ragheb J, McKinney A, Zierau M, Brooks J, Hill-Caruthers M, Iskander M, et al. (2021): Delirium and neuropsychological outcomes in critically Ill patients with COVID-19: a cohort study. BMJ Open 17;11(9):e050045. [CrossRef]
- Quispel-Aggenbach DW, Zuidema SU, Luijendijk HJ (2024): The prognosis of delirium in older outpatients. Psychogeriatrics. 24(2):329-335. [CrossRef]
- Kaźmierski J, Miler P, Pawlak A, Jerczyńska H, Woźniak J, Frankowska E, et al. (2021): Oxidative stress and soluble receptor for advanced glycation end-products play a role in the pathophysiology of delirium after cardiac surgery. Sci Rep. 8;11(1):23646. [CrossRef]
- Kaźmierski J, Miler P, Pawlak A, Jerczyńska H, Woźniak J, Frankowska E, et al. (2021): Elevated Monocyte Chemoattractant Protein-1 as the Independent Risk Factor of Delirium after Cardiac Surgery. A Prospective Cohort Study. J Clin Med. 10(8):1587. [CrossRef]
- Bartel, D. P. (2009). MicroRNAs: target recognition and regulatory functions. Cell 136, 215–233. [CrossRef]
- Cho KHT, Xu B, Blenkiron C, Fraser M. (2019): Emerging Roles of miRNAs in Brain Development and Perinatal Brain Injury. Front Physiol. 28;10:227. [CrossRef]
- Åkerblom M, Sachdeva R, Quintino L, Wettergren EE, Chapman KZ, Manfre G, et al. (2013): Visualization and genetic modification of resident brain microglia using lentiviral vectors regulated by microRNA-9. Nat Commun. 4:1770. [CrossRef]
- Coolen M, Katz S, Bally-Cuif L (2013): miR-9: a versatile regulator of neurogenesis. Front Cell Neurosci. 20;7:220. [CrossRef]
- Zhao X, He X, Han X, Yu Y, Ye F, Chen Y, et al. (2010). MicroRNA-mediated control of oligodendrocyte differentiation. Neuron 65, 612–626. [CrossRef]
- Fu M, Tao J, Wang D, Zhang Z, Wang X, Ji Y, et al. (2020). Downregulation of MicroRNA-34c-5p facilitated neuroinflammation in drug-resistant epilepsy. Brain Res. 15;1749:147130. [CrossRef]
- Tu Y, Hu Y (2021): MiRNA-34c-5p protects against cerebral ischemia/reperfusion injury: involvement of anti-apoptotic and anti-inflammatory activities. Metab Brain Dis. 36(6):1341-1351. [CrossRef]
- Kinoshita C, Kikuchi-Utsumi K, Aoyama K, Suzuki R, Okamoto Y, Matsumura N, et al. (2021): Inhibition of miR-96-5p in the mouse brain increase glutathione levels by altering NOVA1 expression. Commun Biol. 10;4(1):182. [CrossRef]
- Sim SE, Lim CS, Kim JI, Seo D, Chun H, Yu NK, et al. (2016): The Brain-Enriched MicroRNA miR-9-3p Regulates Synaptic Plasticity and Memory. J Neurosci. 17;36(33):8641-52. [CrossRef]
- Yoo AS, Sun AX, Li L, Shcheglovitov A, Portmann T, Li Y, et al. (2011): MicroRNA-mediated conversion of human fibroblasts to neurons. Nature. 476:228–231. [CrossRef]
- Packer AN, Xing Y, Harper SQ, Jones L, Davidson BL (2018): The bifunctional microRNA miR-9/miR-9* regulates REST and CoREST and is downregulated in Huntington's disease. J Neurosci. 28:14341–14346. [CrossRef]
- Cogswell JP, Ward J, Taylor IA, Waters M, Shi Y, Cannon B, et al. (2008): Identification of miRNA changes in Alzheimer's disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimers Dis. 14:27–41. [CrossRef]
- Starhof C, Hejl AM, Heegaard NHH, Carlsen AL, Burton M, Lilje B, et al. (2019): The biomarker potential of cell-free microRNA from cerebrospinal fluid in Parkinsonian Syndromes. Mov Disord. 34(2):246-254. [CrossRef]
- Das Gupta S, Ciszek R, Heiskanen M, Lapinlampi N, Kukkonen J, Leinonen V, et al. (2021): Plasma miR-9-3p and miR-136-3p as Potential Novel Diagnostic Biomarkers for Experimental and Human Mild Traumatic Brain Injury. Int J Mol Sci. 4;22(4):1563. [CrossRef]
- Wang P, Ma H, Zhang Y, Zeng R, Yu J, Liu R, et al. (2020): Plasma Exosome-derived MicroRNAs as Novel Biomarkers of Traumatic Brain Injury in Rats. Int. J. Med Sci. 17, 437–448. [CrossRef]
- Wang B, Yin Z, Lin Y, Deng X, Liu F, Tao H, et al. (2022): Correlation between microRNA-320 and postoperative delirium in patients undergoing tibial fracture internal fixation surgery. BMC Anesthesiol. 22;22(1):75. [CrossRef]
- Chen Y, Zheng J, Chen J (2020): Preoperative Circulating MiR-210, a Risk Factor for Postoperative Delirium Among Elderly Patients with Gastric Cancer Undergoing Curative Resection. Curr Pharm Des. 26(40):5213-5219. [CrossRef]
- Song J, Hu Y, Li H, Huang X, Zheng H, Hu Y, et al. (2018): miR-1303 regulates BBB permeability and promotes CNS lesions following CA16 infections by directly targeting MMP9. Emerg Microbes Infect. 19;7(1):155. [CrossRef]
- Zhu L, Zhou X, Li S, Liu J, Yang J, Fan X, et al. (2020): Zhou S. miR-183-5p attenuates cerebral ischemia injury by negatively regulating PTEN. Mol Med Rep. 22(5):3944-3954. [CrossRef]
- Mao S, Zhao J, Zhang ZJ, Zhao Q (2022): MiR-183-5p overexpression in bone mesenchymal stem cell-derived exosomes protects against myocardial ischemia/reperfusion injury by targeting FOXO1. Immunobiology. 227(3):152204. [CrossRef]
- Roser AE, Caldi Gomes L, Halder R, Jain G, Maass F, Tönges L, et al. (2018): Tatenhorst L, Bähr M, Fischer A, Lingor P. miR-182-5p and miR-183-5p Act as GDNF Mimics in Dopaminergic Midbrain Neurons. Mol Ther Nucleic Acids. 1;11:9-22. [CrossRef]
- Kim JH, Choi JS, Lee BH (2012): PI3K/Akt and MAPK pathways evoke activation of FoxO transcription factor to undergo neuronal apoptosis in brain of the silkworm Bombyx mori (Lepidoptera: Bombycidae). Cell Mol Biol (Noisy-le-grand). 10;Suppl.58:OL1780-5.
- Ding H, Jia Y, Lv H, Chang W, Liu F, et al. (2021): Extracellular vesicles derived from bone marrow mesenchymal stem cells alleviate neuroinflammation after diabetic intracerebral hemorrhage via the miR-183-5p/PDCD4/NLRP3 pathway. Journal of Endocrinological Investigation. 44(12):2685-2698. [CrossRef]
- Zhou Y, Xiao S, Li C, Chen Z, Zhu C, Zhou Q, et al. (2021): Extracellular Vesicle-Encapsulated miR-183-5p from Rhynchophylline-Treated H9c2 Cells Protect against Methamphetamine-Induced Dependence in Mouse Brain by Targeting NRG1. Evid Based Complement Alternat Med. 26;2021:2136076. [CrossRef]
- Miller KE, MacDonald JP, Sullivan L, Venkata LPR, Shi J, Yeates KO, et al. (2022) Salivary miRNA Expression in Children With Persistent Post-concussive Symptoms. Front Public Health. 30;10:890420. [CrossRef]
- Wang S, Greene R, Song Y, Chan C, Lindroth H, Khan S, et al. (2022): Postoperative delirium and its relationship with biomarkers for dementia: a meta-analysis. Int Psychogeriatr. 17:1-14. [CrossRef]
- Noah AM, Almghairbi D, Evley R, Moppett IK (2021): Preoperative inflammatory mediators and postoperative delirium: systematic review and meta-analysis. Br J Anaesth. 127(3):424-434. [CrossRef]
- Ito Y, Suzuki K, Sasaki R, Otani M, Aoki K (2002): Mortality rates from cancer or all causes and SOD activity level and Zn/cu ratio in peripheral blood: population-based follow-up study. J Epidemiol. 12:14–21. [CrossRef]
- Mao C, Yuan JQ, Lv YB, Ainsworth BE, Liu Y, Chen N (2019): Associations between superoxide dismutase, malondialdehyde and all-cause mortality in older adults: a community-based cohort study. BMC Geriatr 19, 104. [CrossRef]
- Fan M, Huang Y, Li K, Yang X, Bai J, Si Q, et al. (2022): Fox-LDL regulates proliferation and apoptosis in VSMCs by controlling the miR-183-5p/FOXO1. Genes Genomics. 44(6):671–81. [CrossRef]
- Sun B, Shan Z, Sun G, Wang X (2021): Micro-RNA-183-5p acts as a potential diagnostic biomarker for atherosclerosis and regulates the growth of vascular smooth muscle cell. J Chin Med Assoc. 84(1):33–7. [CrossRef]
- Zhao X, Jia Y, Chen H, Yao H, Guo W (2019): Plasma-derived exosomal miR-183 associates with protein kinase activity and may serve as a novel predictive biomarker of myocardial ischemic injury. Exp Ther Med. 18(1):179–87. [CrossRef]
- Tong KL, Mahmood Zuhdi AS, Wan Ahmad WA, Vanhoutte PM, de Magalhaes JP, Mustafa MR, et al. (2018): Circulating MicroRNAs in young patients with acute coronary syndrome. Int J Mol Sci. 19(5):1467. [CrossRef]
- Lv D, Guo Y, Zhang L, Li X, Li G (2023): Circulating miR-183-5p levels are positively associated with the presence and severity of coronary artery disease. Front Cardiovasc Med. 15;10:1196348. [CrossRef]
- Folstein MF, Folstein SE, McHugh PR (1975): "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 12(3):189–198.
- American Psychiatric Association. Diagnostic and statistical manual of mental disorders: diagnostic and statistical manual of mental disorders. 5th ed. Arlington (VA): American Psychiatric Association; 2013.
- Ely EW, Margolin R, Francis J, et al.(2001): Evaluation of delirium in critically ill patients: validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Crit Care Med. 29:1370–1379. [CrossRef]
- Kazmierski J, Kowman M, Banach M, Fendler W, Okonski P, Banys A, et al. (2010): The use of DSM-IV and ICD-10 criteria and diagnostic scales for delirium among cardiac surgery patients: results from the IPDACS study. J Neuropsychiatry Clin Neurosci. 22(4):426–432. [CrossRef]
- Kazmierski J, Walkiewicz G, Pawlak A, Miler P, Nowakowska K, Stec-Martyna E, Kulczycka-Wojdala D, Wozniak K, Krejca M, Wilczynski M. Decreased preoperative miR 183-5p expression and an episode of depression are the independent predictors of delirium after cardiac surgery. Neuroscience Applied (2022) 100112. [CrossRef]
| miRNA | Pre-operative level copies/mla |
Post-operative level copies/mla |
|---|---|---|
| miR-9-3p | 79 (13.0 - 172.1) | 101.4 (20.7- 191.9) |
| miR-34c-5p | 12.5 (0.0 - 45.4) | 25.7 (0 -108.1) |
| miR-96-5p | 311.6 (110.2 -696.8) | 156.7 (68.7 – 325.7) |
| miR-183-5p | 78.9 (14.3 – 179.2) | 73.4 (10..4 – 168.2) |
| miR-374-3p | 2.8 (0.0 -30.04) | 0 (0.0 – 16.3) |
| Superoxidase dismutase (ng/ml) | 2.68 (2,06-3.53) | 2.13 (1.62-3.01) |
| Antioxidant activity (µmol/l) | 2.1 (1.3–2.9) | 1.8 (1.2–2.6) |
| Variable | Non-deliriousa | Deliriousa | Effect sizeb | P valuec |
|---|---|---|---|---|
| Preoperative miR-9-3p | 87.4 (34.7-187.2) | 53.8 (5.1-156.6) | 0.32 | 0.39 |
| Preoperative miR-34c-5p | 20.5 (0.0-63.1) | 8.0 (0.0-42.5) | 0.19 | 0.28 |
| Preoperative miR-96-5p | 368.2 (169.7-832.5) | 165.7 (55.0-507.9) | 0.49 | 0.05 |
| Preoperative miR-183-5p | 210.5 (67.7-347.6) | 53.02 (9.6-173.2) | 0.77 | 0.0005 |
| Preoperative miR-374-3p | 9.3 (0.0-39.7) | 0 (0.0-11.2) | 0.34 | 0.26 |
| Postoperative miR-9-3p | 118.5 (45.04-185.9) | 57.13 (0-201.9) | 0.32 | 0.39 |
| Postoperative miR-34c-5p | 51.4 (15.7-121.4) | 7.6 (0-69.6) | 0.56 | 0.009 |
| Postoperative miR-96-5p | 187.2 (96.5-364.2) | 119.2 (33-278,6) | 0.47 | 0.07 |
| Postoperative miR-183-5p | 89.1 (14.5-247.) | 39 (0-98.1) | 0.49 | 0.05 |
| Postoperative miR-374-3p | 0 (0-18.0) | 0 (0-15.4) | 0.09 | 0.99 |
| Variable | Non-deliriousa | Deliriousa | Effect sizeb | P valuec |
|---|---|---|---|---|
| CABG plus valve surgery | 2 (3.3%) | 8 (23.3%) | 0.18 | 0.04 |
| Duration of surgery (h) | 4 (3 – 4.5) | 4 (3.4 – 4.4) | 0.15 | 0.41 |
| Extracorporeal circulation | 40 (66.7%) | 51 (85%) | 0.21 | 0.02 |
| Intraoperative circulatory support | 16 (26.7%) | 17 (28.3%) | 0.24 | 0.16 |
| Post-op. hyperthermia >38℃ | 6 (10%) | 9 (15%) | 0.08 | 0.40 |
| Post-op. pO2 ≤60 mmHg | 5 (8.3%) | 11(18.3%) | 0.15 | 0.10 |
| Post-op. pCO2 ≥45 mmHg | 7 (11.7%) | 18 (30%) | 0.40 | 0.01 |
| Plasma transfusion > 1 unit | 6 (10%) | 9 (15%) | 0.08 | 0.40 |
| Blood transfusion > 4 units | 1 (6.7%) | 5 (8.3%) | 0.15 | 0.21 |
| Variable | Coefficient | Standard Error | OR (95% CI) | P value |
|---|---|---|---|---|
| Depression | 2.53 | 0.79 | 12.6 (2.7-59.2) | < 0.001 |
| Preoperative miR-183-5p | -0.002 | 0.001 | 0.99 (0.995-0.999) | 0.005 |
| Postoperative pCO2 >= 45 | 1.32 | 0.62 | 3.7 (1.1-12.6) | 0.03 |
| Cigarette smoking | 0.91 | 0.46 | 2.4 (1.007-6.15) | 0.05 |
| Gender Female | 1.26 | 0.56 | 3.5 (1.2-10.5) | 0.02 |
| Peripheral vascular disease | 1.38 | 0.68 | 3.9 (1.04-15.2) | 0.04 |
| Constant | -1.005 | 0.40 | - | 0.01 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).