Urinary Aromatic Amino Acid Metabolites Associated With Postoperative Emergence Agitation in Paediatric Patients After General Anaesthesia: Urine Metabolomics Study

Yueyue Li, Jingjie Li, Yuhuan Shi, Xuhui Zhou, Wanqing Feng, Lu Han, Daqing Ma, Hong Jiang, Yongfang Yuan, Yueyue Li, Jingjie Li, Yuhuan Shi, Xuhui Zhou, Wanqing Feng, Lu Han, Daqing Ma, Hong Jiang, Yongfang Yuan

Abstract

Background: Emergence agitation (EA) is very common in paediatric patients during recovery from general anaesthesia, but underlying mechanisms remain unknown. This prospective study was designed to profile preoperative urine metabolites and identify potential biomarkers that can predict the occurrence of EA. Methods: A total of 224 patients were screened for recruitment; of those, preoperative morning urine samples from 33 paediatric patients with EA and 33 non-EA gender- and age-matched patients after being given sevoflurane general anaesthesia were analysed by ultra-high-performance liquid chromatography (UHPLC) coupled with a Q Exactive Plus mass spectrometer. Univariate analysis and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were used to analyse these metabolites. The least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive variables. The predictive model was evaluated through the receiver operating characteristic (ROC) analysis and then further assessed with 10-fold cross-validation. Results: Seventy-seven patients completed the study, of which 33 (42.9%) patients developed EA. EA and non-EA patients had many differences in preoperative urine metabolic profiling. Sixteen metabolites including nine aromatic amino acid metabolites, acylcarnitines, pyridoxamine, porphobilinogen, 7-methylxanthine, and 5'-methylthioadenosine were found associated with an increased risk of EA, and they all exhibited higher levels in the EA group than in the non-EA group. The main metabolic pathways involved in these metabolic changes included phenylalanine, tyrosine and tryptophan metabolisms. Among these potential biomarkers, L-tyrosine had the best predictive value with an odds ratio (OR) (95% CI) of 5.27 (2.20-12.63) and the AUC value of 0.81 (0.70-0.91) and was robust with internal 10-fold cross-validation. Conclusion: Urinary aromatic amino acid metabolites are closely associated with EA in paediatric patients, and further validation with larger cohorts and mechanistic studies is needed. Clinical Trial Registration: clinicaltrials.gov, identifier NCT04807998.

Keywords: aromatic amino acids; emergence agitation; metabolomics; paediatric anaesthesia; prediction model; urine neurotransmitters.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Li, Li, Shi, Zhou, Feng, Han, Ma, Jiang and Yuan.

Figures

FIGURE 1
FIGURE 1
CONSORT flow diagram of the study.
FIGURE 2
FIGURE 2
Score plots of OPLS-DA for the urine metabolomics of emergence agitation (EA) versus the non-EA patients; (A) the positive ionization mode; (B) the negative ionization mode. The permutation test (200 tests total) for the OPLS-DA model; (C) in the positive ionization mode, R2Y and Q2Y were 0.81 and 0.40, respectively; (D) in the negative ionization mode, R2Y and Q2Y were 0.71 and 0.22, respectively.
FIGURE 3
FIGURE 3
Heat map of differential metabolites between emergence agitation (EA) and non-EA patients.
FIGURE 4
FIGURE 4
Performance of L-tyrosine to predict emergence agitation (EA) with the receiver operating characteristic (ROC) analysis and further internal cross-validation.

References

    1. Carneiro G., Radcenco A. L., Evaristo J., Monnerat G. (2019). Novel Strategies for Clinical Investigation and Biomarker Discovery: a Guide to Applied Metabolomics. Horm. Mol. Biosl. Clin. Investig. 38, e0045. 10.1515/hmbci-2018-0045
    1. Chandler J. R., Myers D., Mehta D., Whyte E., Groberman M. K., Montgomery C. J., et al. (2013). Emergence Delirium in Children: a Randomized Trial to Compare Total Intravenous Anesthesia with Propofol and Remifentanil to Inhalational Sevoflurane Anesthesia. Paediatr. Anaesth. 23 (4), 309–315. 10.1111/pan.12090
    1. Chekhonin V. P., Baklaushev V. P., Kogan B. M., Savchenko E. A., Lebedev S. V., Man'kovskaya I. V., et al. (2000). Catecholamines and Their Metabolites in the Brain and Urine of Rats with Experimental Parkinson's Disease. Bull. Exp. Biol. Med. 130 (8), 805–809. 10.1007/BF02766101
    1. Cohen I. T., Finkel J. C., Hannallah R. S., Hummer K. A., Patel K. M. (2003). Rapid Emergence Does Not Explain Agitation Following Sevoflurane Anaesthesia in Infants and Children: a Comparison with Propofol. Paediatr. Anaesth. 13 (1), 63–67. 10.1046/j.1460-9592.2003.00948.x
    1. Curto M., Lionetto L., Fazio F., Mitsikostas D. D., Martelletti P. (2015). Fathoming the Kynurenine Pathway in Migraine: Why Understanding the Enzymatic Cascades Is Still Critically Important. Intern Emerg. Med. 10 (4), 413–421. 10.1007/s11739-015-1208-6
    1. Dehaven C. D., Evans A. M., Dai H., Lawton K. A. (2010). Organization of GC/MS and LC/MS Metabolomics Data into Chemical Libraries. J. Cheminform 2 (1), 9. 10.1186/1758-2946-2-9
    1. Fazio F., Lionetto L., Curto M., Iacovelli L., Copeland C. S., Neale S. A., et al. (2017). Cinnabarinic Acid and Xanthurenic Acid: Two Kynurenine Metabolites that Interact with Metabotropic Glutamate Receptors. Neuropharmacology 112 (Pt B), 365–372. 10.1016/j.neuropharm.2016.06.020
    1. Fernstrom J. D., Fernstrom M. H. (2007). Tyrosine, Phenylalanine, and Catecholamine Synthesis and Function in the Brain. J. Nutr. 137 (6 Suppl. 1), 1539S–1548S. 10.1093/jn/137.6.1539S
    1. Gevi F., Zolla L., Gabriele S., Persico A. M. (2016). Urinary Metabolomics of Young Italian Autistic Children Supports Abnormal Tryptophan and Purine Metabolism. Mol. Autism 7 (7), 47. 10.1186/s13229-016-0109-5
    1. Gibert S., Sabourdin N., Louvet N., Moutard M. L., Piat V., Guye M. L., et al. (2012). Epileptogenic Effect of Sevoflurane: Determination of the Minimal Alveolar Concentration of Sevoflurane Associated with Major Epileptoid Signs in Children. Anesthesiology 117 (6), 1253–1261. 10.1097/ALN.0b013e318273e272
    1. Guo Y., Zhang Y., Jia P., Wang W., Zhou Q., Sun L., et al. (2017). Preoperative Serum Metabolites Are Associated with Postoperative Delirium in Elderly Hip-Fracture Patients. J. Gerontol. A Biol. Sci. Med. Sci. 72 (12), 1689–1696. 10.1093/gerona/glx001
    1. Hackstadt A. J., Hess A. M. (2009). Filtering for Increased Power for Microarray Data Analysis. BMC Bioinforma. 10, 11. 10.1186/1471-2105-10-11
    1. Han Y., Zhang W., Liu J., Song Y., Liu T., Li Z., et al. (2020). Metabolomic and Lipidomic Profiling of Preoperative CSF in Elderly Hip Fracture Patients with Postoperative Delirium. Front. Aging Neurosci. 12 (12), 570210. 10.3389/fnagi.2020.570210
    1. Jacob Z., Li H., Makaryus R., Zhang S., Reinsel R., Lee H., et al. (2012). Metabolomic Profiling of Children's Brains Undergoing General Anesthesia with Sevoflurane and Propofol. Anesthesiology 117, 1062–1071. 10.1097/ALN.0b013e31826be417
    1. Kang W., Lu D., Yang X., Ma W., Chen X., Chen K., et al. (2020). Sevoflurane Induces Hippocampal Neuronal Apoptosis by Altering the Level of Neuropeptide Y in Neonatal Rats. Neurochem. Res. 45 (9), 1986–1996. 10.1007/s11064-020-03028-9
    1. Kennedy A. D., Pappan K. L., Donti T., Delgado M. R., Shinawi M., Pearson T. S., et al. (2019). 2-Pyrrolidinone and Succinimide as Clinical Screening Biomarkers for GABA-Transaminase Deficiency: Anti-seizure Medications Impact Accurate Diagnosis. Front. Neurosci. 13, 394. 10.3389/fnins.2019.00394
    1. Kheirandish-Gozal L., McManus C. J. T., Kellermann G. H., Samiei A., Gozal D. (2013). Urinary Neurotransmitters Are Selectively Altered in Children with Obstructive Sleep Apnea and Predict Cognitive Morbidity. Chest 143 (6), 1576–1583. 10.1378/chest.12-2606
    1. Koch S., Rupp L., Prager C., Wernecke K. D., Kramer S., Fahlenkamp A., et al. (2018). Emergence Delirium in Children Is Related to Epileptiform Discharges during Anaesthesia Induction: An Observational Study. Eur. J. Anaesthesiol. 35 (12), 929–936. 10.1097/EJA.0000000000000867
    1. Lavarello C., Barco S., Bartolucci M., Panfoli I., Magi E., Tripodi G., et al. (2021). Development of an Accurate Mass Retention Time Database for Untargeted Metabolomic Analysis and its Application to Plasma and Urine Pediatric Samples. Molecules 26 (14), 4256. 10.3390/molecules26144256
    1. Lee S. J., Sung T. Y. (2020). Emergence Agitation: Current Knowledge and Unresolved Questions. Korean J. Anesthesiol. 73 (6), 471–485. 10.4097/kja.20097
    1. Lee S. M., Lee Y. S., Choi J. H., Park S. G., Choi I. W., Joo Y. D., et al. (2010). Tryptophan Metabolite 3-hydroxyanthranilic Acid Selectively Induces Activated T Cell Death via Intracellular GSH Depletion. Immunol. Lett. 132 (1-2), 53–60. 10.1016/j.imlet.2010.05.008
    1. Liu F., Rainosek S. W., Frisch-Daiello J. L., Patterson T. A., Paule M. G., Slikker W., Jr., et al. (2015). Potential Adverse Effects of Prolonged Sevoflurane Exposure on Developing Monkey Brain: From Abnormal Lipid Metabolism to Neuronal Damage. Toxicol. Sci. 147 (2), 562–572. 10.1093/toxsci/kfv150
    1. Lynn-Bullock C. P., Welshhans K., Pallas S. L., Katz P. S. (2004). The Effect of Oral 5-HTP Administration on 5-HTP and 5-HT Immunoreactivity in Monoaminergic Brain Regions of Rats. J. Chem. Neuroanat. 27 (2), 129–138. 10.1016/j.jchemneu.2004.02.003
    1. Maldonado J. R. (2013). Neuropathogenesis of Delirium: Review of Current Etiologic Theories and Common Pathways. Am. J. Geriatr. Psychiatry 21 (12), 1190–1222. 10.1016/j.jagp.2013.09.005
    1. Nyamundanda G., Gormley I. C., Fan Y., Gallagher W. M., Brennan L. (2013). MetSizeR: Selecting the Optimal Sample Size for Metabolomic Studies Using an Analysis Based Approach. BMC Bioinforma. 14, 338. 10.1186/1471-2105-14-338
    1. Pan J. X., Xia J. J., Deng F. L., Liang W. W., Wu J., Yin B. M., et al. (2018). Diagnosis of Major Depressive Disorder Based on Changes in Multiple Plasma Neurotransmitters: a Targeted Metabolomics Study. Transl. Psychiatry 8 (1), 130. 10.1038/s41398-018-0183-x
    1. Parra M., Stahl S., Hellmann H. (2018). Vitamin B₆ and its Role in Cell Metabolism and Physiology. Cells 7 (7), 84. 10.3390/cells7070084
    1. Rosa A. P., Jacques C. E., Moraes T. B., Wannmacher C. M., Dutra A. M., Dutra-Filho C. S. (2012). Phenylpyruvic Acid Decreases Glucose-6-Phosphate Dehydrogenase Activity in Rat Brain. Cell. Mol. Neurobiol. 32 (7), 1113–1118. 10.1007/s10571-012-9834-2
    1. Silva-Adaya D., Pérez-De La CruzCruz V. V., Herrera-Mundo M. N., Mendoza-Macedo K., Villeda-Hernández J., Binienda Z., et al. (2008). Excitotoxic Damage, Disrupted Energy Metabolism, and Oxidative Stress in the Rat Brain: Antioxidant and Neuroprotective Effects of L-Carnitine. J. Neurochem. 105 (3), 677–689. 10.1111/j.1471-4159.2007.05174.x
    1. Stoicea N., McVicker S., Quinones A., Agbenyefia P., Bergese S. D. (2014). Delirium-biomarkers and Genetic Variance. Front. Pharmacol. 5, 75. 10.3389/fphar.2014.00075
    1. Vlajkovic G. P., Sindjelic R. P. (2007). Emergence Delirium in Children: Many Questions, Few Answers. Anesth. Analg. 104, 84–91. 10.1213/01.ane.0000250914.91881.a8
    1. Voepel-Lewis T., Malviya S., Tait A. R. (2003). A Prospective Cohort Study of Emergence Agitation in the Pediatric Postanesthesia Care Unit. Anesth. Analg. 96 (6), 1625. 10.1213/01.ANE.0000062522.21048.61
    1. Wang C., Liu F., Frisch-Daiello J. L., Martin S., Patterson T. A., Gu Q., et al. (2018). Lipidomics Reveals a Systemic Energy Deficient State that Precedes Neurotoxicity in Neonatal Monkeys after Sevoflurane Exposure. Anal. Chim. Acta 1037, 87–96. 10.1016/j.aca.2017.11.052
    1. Wang L. J., Chou W. J., Tsai C. S., Lee M. J., Lee S. Y., Hsu C. W., et al. (2021). Novel Plasma Metabolite Markers of Attention-Deficit/hyperactivity Disorder Identified Using High-Performance Chemical Isotope Labelling-Based Liquid Chromatography-Mass Spectrometry. World J. Biol. Psychiatry 22 (2), 139–148. 10.1080/15622975.2020.1762930
    1. Wang Q., Zhou J., Liu T., Yang N., Mi X., Han D., et al. (2021). Predictive Value of Preoperative Profiling of Serum Metabolites for Emergence Agitation after General Anesthesia in Adult Patients. Front. Mol. Biosci. 8, 739227. 10.3389/fmolb.2021.739227
    1. Watne L. O., Idland A. V., Fekkes D., Raeder J., Frihagen F., Ranhoff A. H., et al. (2016). Increased CSF Levels of Aromatic Amino Acids in Hip Fracture Patients with Delirium Suggests Higher Monoaminergic Activity. BMC Geriatr. 16, 16149. 10.1186/s12877-016-0324-0
    1. Watzlawik J. O., Wootla B., Rodriguez M. (2016). Tryptophan Catabolites and Their Impact on Multiple Sclerosis Progression. Curr. Pharm. Des. 22 (8), 1049–1059. 10.2174/1381612822666151215095940
    1. Westphalen R. I., Desai K. M., Hemmings H. C., Jr. (2013). Presynaptic Inhibition of the Release of Multiple Major Central Nervous System Neurotransmitter Types by the Inhaled Anaesthetic Isoflurane. Br. J. Anaesth. 110 (4), 592–599. 10.1093/bja/aes448
    1. Woods S. K., Meyer J. S. (1991). Exogenous Tyrosine Potentiates the Methylphenidate-Induced Increase in Extracellular Dopamine in the Nucleus Accumbens: a Microdialysis Study. Brain Res. 560 (1-2), 97–105. 10.1016/0006-8993(91)91220-u
    1. Yu M. C., Wang T. M., Chiou Y. H., Yu M. K., Lin C. F., Chiu C. Y. (2021). Urine Metabolic Phenotyping in Children with Nocturnal Enuresis and Comorbid Neurobehavioral Disorders. Sci. Rep. 11 (1), 16592. 10.1038/s41598-021-96104-1
    1. Zanelli S. A., Solenski N. J., Rosenthal R. E., Fiskum G. (2005). Mechanisms of Ischemic Neuroprotection by Acetyl-L-Carnitine. Ann. N. Y. Acad. Sci. 1053, 153–161. 10.1196/annals.1344.013
    1. Zhou X., Liu L., Lan X., Cohen D., Zhang Y., Ravindran A. V., et al. (2019). Polyunsaturated Fatty Acids Metabolism, Purine Metabolism and Inosine as Potential Independent Diagnostic Biomarkers for Major Depressive Disorder in Children and Adolescents. Mol. Psychiatry 24 (10), 1478–1488. 10.1038/s41380-018-0047-z
    1. Zhu Y., Barupal D. K., Ngo A. L., Quesenberry C. P., Feng J., Fiehn O., et al. (2022). Predictive Metabolomic Markers in Early to Mid-pregnancy for Gestational Diabetes: A Prospective Test and Validation Study. Diabetes 21, 1093. 10.2337/db21-1093

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