NeurimmiRs and Postoperative Delirium in Elderly Patients Undergoing Total Hip/Knee Replacement: A Pilot Study

Rui Dong, Lingling Sun, Yayuan Lu, Xi Yang, Mian Peng, Zongze Zhang, Rui Dong, Lingling Sun, Yayuan Lu, Xi Yang, Mian Peng, Zongze Zhang

Abstract

Objective: Postoperative delirium (POD) is a frequent complication after surgery and its occurrence is associated with poor outcomes. The pathophysiology of this complication is not clear, but identification of risk factors is important for positive postoperative outcomes. The purpose of this study was to investigate the associations between the preoperative expression levels of microRNA (miR)-146a, miR-125b, and miR-181c in cerebrospinal fluid (CSF) and serum and the development and severity of POD. Methods: Forty elderly patients aged 65 years old and older admitted for elective total hip/knee replacement under spinal anesthesia. Preoperatively, baseline cognitive function was assessed using the Mini-Mental State Examination. Each patient was interviewed daily on the first and second postoperative days. Delirium was diagnosed using the Confusion Assessment Method, and delirium severity was measured using the Memorial Delirium Assessment Scale (MDAS). Preoperative serum and CSF miR levels were determined by quantitative real-time PCR (qRT-PCR). Results: POD was detected in 27.5% (11/40) of patients. Up-regulation of miR-146a and miR-181c in CSF and down-regulation of miR-146a in serum were observed preoperatively in patients who developed POD, while patients with and without POD did not differ in serum or CSF levels of miR-125b. Delirious patients had higher CSF/serum ratios of miR-146a and miR-181c levels than non-delirious patients. The lower CSF miR-146a and CSF/serum miR-146a ratios were significantly associated with milder POD severity, represented by a lower MDAS score. Conclusion: The dysregulation of preoperative miR-146a and miR-181c in CSF and serum was associated with the development and severity of POD. These NeurimmiRs might participate in the neuropathogenesis of POD, pending further investigations. Clinical trial registration: this study was registered at ClinicalTrials.gov (NCT02817386).

Keywords: elderly patients; microRNA; neuroinflammation; postoperative delirium; surgery.

Figures

FIGURE 1
FIGURE 1
Flow diagram. The flow diagram shows that 86 patients were initially screened for the studies, and 40 patients were finally included in the data analysis.
FIGURE 2
FIGURE 2
Expression of candidate NeurimmiRs in the CSF and serum of patients with or without POD. Scatter plots of mean Ct-values of U6 (A) and expression levels of miR-146a (B), miR-125b (C), and miR-181c (D) in the CSF and serum of patients with or without POD. Rel was calculated after normalization using U6 snRNA. The black horizontal lines represent median Rel values ± 95% CIs. Each point represents the mean of triplicate samples. P-values were determined using the Mann–Whitney U-test. POD, postoperative delirium; Rel, relative expression level; CSF, cerebrospinal fluid.
FIGURE 3
FIGURE 3
POD severity in the first quartile and the combination of the other three quartiles of levels of miRs and miR CSF/serum ratios. We found that the median of the highest MDAS score (4, 2–5) of the patients in the first quartile of miRNA-146a in CSF was significantly lower than that of the patients in the combination of the second, third, and fourth quartiles of miRNA-146a in CSF (9, 6–13) (A). In contrast, the median of the highest MDAS score (12, 8–14) of the patients in the first quartile of miRNA-146a in serum was significantly higher than that of the patients in the combination of the second, third, and fourth quartiles of miRNA-146a in serum (6, 5–8) (B). The median of the highest MDAS score in the first quartile of miR-146a cell-free CSF/serum ratio (5, 2–7) was significantly lower than that of the patients in the combination of the second, third, and fourth quartiles of miR-146a CSF/serum ratio (9, 6–13) (C). No significant difference in the highest MDAS score was observed between the patients in the first quartile and the patients in the combination of the second, third, and fourth quartiles of CSF miR-181c or CSF/serum miR-181c ratio (D,E). The black horizontal lines represent median MDAS scores ± interquartile ranges. Each point represents the highest MDAS score. P-values were determined using the Mann–Whitney U-test. POD, postoperative delirium; CSF, cerebrospinal fluid; MDAS, Memorial Delirium Assessment Scale.

References

    1. Acharya N. K., Goldwaser E. L., Forsberg M. M., Godsey G. A., Johnson C. A., Sarkar A., et al. (2015). Sevoflurane and Isoflurane induce structural changes in brain vascular endothelial cells and increase blood-brain barrier permeability: possible link to postoperative delirium and cognitive decline. Brain Res. 1620 29–41. 10.1016/j.brainres.2015.04.054
    1. Alagiakrishnan K., Wiens C. A. (2004). An approach to drug induced delirium in the elderly. Postgrad. Med. J. 80 388–393. 10.1136/pgmj.2003.017236
    1. Alvarez-Erviti L., Seow Y., Yin H., Betts C., Lakhal S., Wood M. J. (2011). Delivery of siRNA to the mouse brain by systemic injection of targeted exosomes. Nat. Biotechnol. 29 341–345. 10.1038/nbt.1807
    1. Bhaumik D., Scott G. K., Schokrpur S., Patil C. K., Orjalo A. V., Rodier F., et al. (2009). MicroRNAs miR-146a/b negatively modulate the senescence-associated inflammatory mediators IL-6 and IL-8. Aging 1 402–411. 10.18632/aging.100042
    1. Boldin M. P., Baltimore D. (2012). MicroRNAs, new effectors and regulators of NF-kappaB. Immunol. Rev. 246 205–220. 10.1111/j.1600-065X.2011.01089.x
    1. Burgos K. L., Javaherian A., Bomprezzi R., Ghaffari L., Rhodes S., Courtright A., et al. (2013). Identification of extracellular miRNA in human cerebrospinal fluid by next-generation sequencing. RNA 19 712–722. 10.1261/rna.036863.112036863.112
    1. Cerejeira J., Firmino H., Vaz-Serra A., Mukaetova-Ladinska E. B. (2010). The neuroinflammatory hypothesis of delirium. Acta Neuropathol. 119 737–754. 10.1007/s00401-010-0674-1
    1. Chung D., Sue A., Hughes S., Simmons J., Hailu T., Swift C., et al. (2016). Impact of race/ethnicity on pain management outcomes in a community-based teaching hospital following inpatient palliative care consultation. Cureus 8:e823 10.7759/cureus.823
    1. Cogswell J. P., Ward J., Taylor I. A., 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.
    1. Dantzer R., O’Connor J. C., Freund G. G., Johnson R. W., Kelley K. W. (2008). From inflammation to sickness and depression: when the immune system subjugates the brain. Nat. Rev. Neurosci. 9 46–56. 10.1038/nrn2297
    1. Davenport D. L., Bowe E. A., Henderson W. G., Khuri S. F., Mentzer R. M., Jr. (2006). National Surgical Quality Improvement Program (NSQIP) risk factors can be used to validate American Society of Anesthesiologists Physical Status Classification (ASA PS) levels. Ann. Surg. 243 636–641; discussion 641–634. 10.1097/
    1. Davis D. H., Muniz Terrera G., Keage H., Rahkonen T., Oinas M., Matthews F. E., et al. (2012). Delirium is a strong risk factor for dementia in the oldest-old: a population-based cohort study. Brain 135(Pt 9), 2809–2816. 10.1093/brain/aws190
    1. Davis D. H., Skelly D. T., Murray C., Hennessy E., Bowen J., Norton S., et al. (2015). Worsening cognitive impairment and neurodegenerative pathology progressively increase risk for delirium. Am. J. Geriatr. Psychiatry 23 403–415. 10.1016/j.jagp.2014.08.005
    1. Denk J., Boelmans K., Siegismund C., Lassner D., Arlt S., Jahn H. (2015). MicroRNA profiling of CSF reveals potential biomarkers to detect Alzheimer‘s disease. PLoS ONE 10:e0126423 10.1371/journal.pone.0126423
    1. Duijvesz D., Luider T., Bangma C. H., Jenster G. (2011). Exosomes as biomarker treasure chests for prostate cancer. Eur. Urol. 59 823–831.10.1016/j.eururo.2010.12.031
    1. Gallego J. A., Gordon M. L., Claycomb K., Bhatt M., Lencz T., Malhotra A. K. (2012). In vivo microRNA detection and quantitation in cerebrospinal fluid. J. Mol. Neurosci. 47 243–248. 10.1007/s12031-012-9731-7
    1. Garden G. A., Moller T. (2006). Microglia biology in health and disease. J Neuroimmune Pharmacol. 1 127–137. 10.1007/s11481-006-9015-5
    1. Geekiyanage H., Jicha G. A., Nelson P. T., Chan C. (2012). Blood serum miRNA: non-invasive biomarkers for Alzheimer’s disease. Exp. Neurol. 235 491–496. 10.1016/j.expneurol.2011.11.026
    1. Gombar S., Jung H. J., Dong F., Calder B., Atzmon G., Barzilai N., et al. (2012). Comprehensive microRNA profiling in B-cells of human centenarians by massively parallel sequencing. BMC Genomics 13:353 10.1186/1471-2164-13-353
    1. Gunther M. L., Morandi A., Krauskopf E., Pandharipande P., Girard T. D., Jackson J. C., et al. (2012). The association between brain volumes, delirium duration, and cognitive outcomes in intensive care unit survivors: the VISIONS cohort magnetic resonance imaging study∗. Crit. Care Med. 40 2022–2032. 10.1097/CCM.0b013e318250acc0
    1. Hala M. (2007). Pathophysiology of postoperative delirium: systemic inflammation as a response to surgical trauma causes diffuse microcirculatory impairment. Med. Hypotheses 68 194–196. 10.1016/j.mehy.2006.07.003
    1. Hannafon B. N., Ding W. Q. (2013). Intercellular communication by exosome-derived microRNAs in cancer. Int. J. Mol. Sci. 14 14240–14269.10.3390/ijms140714240
    1. Hutchison E. R., Kawamoto E. M., Taub D. D., Lal A., Abdelmohsen K., Zhang Y., et al. (2013). Evidence for miR-181 involvement in neuroinflammatory responses of astrocytes. Glia 61 1018–1028. 10.1002/glia.22483
    1. Inouye S. K., Charpentier P. A. (1996). Precipitating factors for delirium in hospitalized elderly persons. Predictive model and interrelationship with baseline vulnerability. JAMA 275 852–857.
    1. Inouye S. K., Ferrucci L. (2006). Elucidating the pathophysiology of delirium and the interrelationship of delirium and dementia. J. Gerontol. A Biol. Sci. Med. Sci. 61 1277–1280.
    1. Inouye S. K., van Dyck C. H., Alessi C. A., Balkin S., Siegal A. P., Horwitz R. I. (1990). Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Ann. Intern. Med. 113 941–948.
    1. Ishii K., Makita T., Yamashita H., Matsunaga S., Akiyama D., Toba K., et al. (2016). Total intravenous anesthesia with propofol is associated with a lower rate of postoperative delirium in comparison with sevoflurane anesthesia in elderly patients. J. Clin. Anesth. 33 428–431. 10.1016/j.jclinane.2016.04.043
    1. Iyer A., Zurolo E., Prabowo A., Fluiter K., Spliet W. G., van Rijen P. C., et al. (2012). MicroRNA-146a: a key regulator of astrocyte-mediated inflammatory response. PLoS ONE 7:e44789 10.1371/journal.pone.0044789
    1. Kharaziha P., Ceder S., Li Q., Panaretakis T. (2012). Tumor cell-derived exosomes: a message in a bottle. Biochim. Biophys. Acta 1826 103–111.10.1016/j.bbcan.2012.03.006
    1. Kiko T., Nakagawa K., Tsuduki T., Furukawa K., Arai H., Miyazawa T. (2014). MicroRNAs in plasma and cerebrospinal fluid as potential markers for Alzheimer’s disease. J. Alzheimers Dis. 39 253–259. 10.3233/JAD-130932
    1. Leung J., Leung V., Leung C. M., Pan P. C. (2008). Clinical utility and validation of two instruments (the confusion assessment method algorithm and the chinese version of nursing delirium screening scale) to detect delirium in geriatric inpatients. Gen. Hosp. Psychiatry 30 171–176. 10.1016/j.genhosppsych.2007.12.007
    1. Leung J. M., Sands L. P., Lim E., Tsai T. L., Kinjo S. (2013). Does preoperative risk for delirium moderate the effects of postoperative pain and opiate use on postoperative delirium? Am. J. Geriatr. Psychiatry 21 946–956. 10.1016/j.jagp.2013.01.069
    1. Leung J. M., Sands L. P., Newman S., Meckler G., Xie Y., Gay C., et al. (2015). Preoperative sleep disruption and postoperative delirium. J. Clin. Sleep Med. 11 907–913. 10.5664/jcsm.4944
    1. Liu L. L., Leung J. M. (2000). Predicting adverse postoperative outcomes in patients aged 80 years or older. J. Am. Geriatr. Soc. 48 405–412.
    1. Lukiw W. J., Alexandrov P. N. (2012). Regulation of complement factor H (CFH) by multiple miRNAs in Alzheimer’s disease (AD) brain. Mol. Neurobiol. 46 11–19. 10.1007/s12035-012-8234-4
    1. Lukiw W. J., Andreeva T. V., Grigorenko A. P., Rogaev E. I. (2012). Studying micro RNA function and dysfunction in Alzheimer’s disease. Front. Genet. 3:327 10.3389/fgene.2012.00327
    1. MacLullich A. M., Edelshain B. T., Hall R. J., de Vries A., Howie S. E., Pearson A., et al. (2011). Cerebrospinal fluid interleukin-8 levels are higher in people with hip fracture with perioperative delirium than in controls. J. Am. Geriatr. Soc. 59 1151–1153. 10.1111/j.1532-5415.2011.03428.x
    1. Maclullich A. M., Ferguson K. J., Miller T., de Rooij S. E., Cunningham C. (2008). Unravelling the pathophysiology of delirium: a focus on the role of aberrant stress responses. J. Psychosom. Res. 65 229–238. 10.1016/j.jpsychores.2008.05.019
    1. Marcantonio E., Ta T., Duthie E., Resnick N. M. (2002). Delirium severity and psychomotor types: their relationship with outcomes after hip fracture repair. J. Am. Geriatr. Soc. 50 850–857.
    1. Marcantonio E. R., Goldman L., Mangione C. M., Ludwig L. E., Muraca B., Haslauer C. M., et al. (1994). A clinical prediction rule for delirium after elective noncardiac surgery. JAMA 271 134–139.
    1. Mikecin L., Krizmaric M., Stepan Giljevic J., Gjurasin M., Kern J., Lenicek Krleza J., et al. (2013). Pseudocholinesterase activity in cerebrospinal fluid as a biomarker of solid central nervous system tumors in children. Croat. Med. J. 54 429–435.
    1. Mitchell P. S., Parkin R. K., Kroh E. M., Fritz B. R., Wyman S. K., Pogosova-Agadjanyan E. L., et al. (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proc. Natl. Acad. Sci. U.S.A. 105 10513–10518. 10.1073/pnas.0804549105
    1. Muller M., Kuiperij H. B., Claassen J. A., Kusters B., Verbeek M. M. (2014). MicroRNAs in Alzheimer’s disease: differential expression in hippocampus and cell-free cerebrospinal fluid. Neurobiol. Aging 35 152–158. 10.1016/j.neurobiolaging.2013.07.005
    1. Murray C., Sanderson D. J., Barkus C., Deacon R. M., Rawlins J. N., Bannerman D. M., et al. (2012). Systemic inflammation induces acute working memory deficits in the primed brain: relevance for delirium. Neurobiol. Aging 33 603–616. 10.1016/j.neurobiolaging.2010.04.002
    1. Olivieri F., Rippo M. R., Procopio A. D., Fazioli F. (2013). Circulating inflamma-miRs in aging and age-related diseases. Front. Genet. 4:12110.3389/fgene.2013.00121
    1. Perry V. H. (2004). The influence of systemic inflammation on inflammation in the brain: implications for chronic neurodegenerative disease. Brain Behav. Immun. 18 407–413. 10.1016/j.bbi.2004.01.004
    1. Raposo G., Stoorvogel W. (2013). Extracellular vesicles: exosomes, microvesicles, and friends. J. Cell Biol. 200 373–383. 10.1083/jcb.201211138
    1. Rudolph J. L., Marcantonio E. R. (2011). Review articles: postoperative delirium: acute change with long-term implications. Anesth. Analg. 112 1202–1211. 10.1213/ANE.0b013e3182147f6d
    1. Saba R., Goodman C. D., Huzarewich R. L., Robertson C., Booth S. A. (2008). A miRNA signature of prion induced neurodegeneration. PLoS ONE 3:e3652 10.1371/journal.pone.0003652
    1. Saba R., Gushue S., Huzarewich R. L., Manguiat K., Medina S., Robertson C., et al. (2012). MicroRNA 146a (miR-146a) is over-expressed during prion disease and modulates the innate immune response and the microglial activation state. PLoS ONE 7:e30832 10.1371/journal.pone.0030832
    1. Schmidt C., Gerlach N., Schmitz M., Thom T., Kramer K., Friede T., et al. (2015). Baseline CSF/serum-ratio of apolipoprotein E and rate of differential decline in Alzheimer’s disease. J. Alzheimers Dis. 48 189–196. 10.3233/JAD-150286
    1. Schuurmans M. J., Deschamps P. I., Markham S. W., Shortridge-Baggett L. M., Duursma S. A. (2003). The measurement of delirium: review of scales. Res. Theory Nurs. Pract. 17 207–224.
    1. Scott J. E., Mathias J. L., Kneebone A. C. (2015). Incidence of delirium following total joint replacement in older adults: a meta-analysis. Gen. Hosp. Psychiatry 37 223–229. 10.1016/j.genhosppsych.2015.02.004
    1. Shi Z., Wu Y., Li C., Fu S., Li G., Zhu Y., et al. (2014). Using the Chinese version of Memorial Delirium Assessment Scale to describe postoperative delirium after hip surgery. Front. Aging Neurosci. 6:297 10.3389/fnagi.2014.00297
    1. Shim J. J., Leung J. M. (2012). An update on delirium in the postoperative setting: prevention, diagnosis and management. Best Pract. Res. Clin. Anaesthesiol. 26 327–343. 10.1016/j.bpa.2012.08.003
    1. Sieber F. E., Barnett S. R. (2011). Preventing postoperative complications in the elderly. Anesthesiol. Clin. 29 83–97. 10.1016/j.anclin.2010.11.011
    1. Singer O., Marr R. A., Rockenstein E., Crews L., Coufal N. G., Gage F. H., et al. (2005). Targeting BACE1 with siRNAs ameliorates Alzheimer disease neuropathology in a transgenic model. Nat. Neurosci. 8 1343–1349.10.1038/nn1531
    1. Soreq H., Wolf Y. (2011). NeurimmiRs: microRNAs in the neuroimmune interface. Trends Mol. Med. 17 548–555. 10.1016/j.molmed.2011.06.00906.009
    1. Street J. M., Barran P. E., Mackay C. L., Weidt S., Balmforth C., Walsh T. S., et al. (2012). Identification and proteomic profiling of exosomes in human cerebrospinal fluid. J. Transl. Med. 10:5 10.1186/1479-5876-10-55876-10-5
    1. Tan L., Yu J. T., Hu N., Tan L. (2013). Non-coding RNAs in Alzheimer’s disease. Mol. Neurobiol. 47 382–393. 10.1007/s12035-012-8359-5359-5
    1. Tan L., Yu J. T., Liu Q. Y., Tan M. S., Zhang W., Hu N., et al. (2014). Circulating miR-125b as a biomarker of Alzheimer’s disease. J. Neurol. Sci. 336 52–56. 10.1016/j.jns.2013.10.002
    1. Teeling J. L., Perry V. H. (2009). Systemic infection and inflammation in acute CNS injury and chronic neurodegeneration: underlying mechanisms. Neuroscience 158 1062–1073. 10.1016/j.neuroscience.2008.07.031
    1. van Gool W. A., van de Beek D., Eikelenboom P. (2010). Systemic infection and delirium: when cytokines and acetylcholine collide. Lancet 375 773–775. 10.1016/S0140-6736(09)61158-2
    1. Weber J. A., Baxter D. H., Zhang S., Huang D. Y., Huang K. H., Lee M. J., et al. (2010). The microRNA spectrum in 12 body fluids. Clin. Chem. 56 1733–1741. 10.1373/clinchem.2010.147405
    1. Xie Z., Swain C. A., Ward S. A., Zheng H., Dong Y., Sunder N., et al. (2014). Preoperative cerebrospinal fluid beta-Amyloid/Tau ratio and postoperative delirium. Ann. Clin. Transl. Neurol. 1 319–328. 10.1002/acn3.58
    1. Xu G., Meyer J. S., Thornby J., Chowdhury M., Quach M. (2002). Screening for mild cognitive impairment (MCI) utilizing combined mini-mental-cognitive capacity examinations for identifying dementia prodromes. Int. J. Geriatr. Psychiatry 17 1027–1033. 10.1002/gps.744
    1. Yagi Y., Ohkubo T., Kawaji H., Machida A., Miyata H., Goda S., et al. (2017). Next-generation sequencing-based small RNA profiling of cerebrospinal fluid exosomes. Neurosci. Lett. 636 48–57. 10.1016/j.neulet.2016.10.042
    1. Zhang L., Dong L. Y., Li Y. J., Hong Z., Wei W. S. (2012). The microRNA miR-181c controls microglia-mediated neuronal apoptosis by suppressing tumor necrosis factor. J. Neuroinflammation 9 211 10.1186/1742-2094-9-211
    1. Zhang L., Li Y. J., Wu X. Y., Hong Z., Wei W. S. (2015). MicroRNA-181c negatively regulates the inflammatory response in oxygen-glucose-deprived microglia by targeting Toll-like receptor 4. J. Neurochem. 132 713–723.10.1111/jnc.13021
    1. Zuberi M., Khan I., Mir R., Gandhi G., Ray P. C., Saxena A. (2016). Utility of serum miR-125b as a diagnostic and prognostic indicator and its alliance with a panel of tumor suppressor genes in epithelial ovarian cancer. PLoS ONE 11:e0153902 10.1371/journal.pone.0153902

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