Carnitine is causally associated with susceptibility and severity of sepsis: a Mendelian randomization study

Abstract

Background: Energy metabolism disorders contribute to the development of sepsis. Carnitine is essential for fatty acid metabolism and energy production. Therefore, we aimed to explore whether there is a causal relationship between carnitine levels and sepsis.

Methods: Two-sample Mendelian randomization (MR) analysis was performed. The single nucleotide polymorphisms (SNPs) of carnitine from the genome-wide association (GWAS) study were used as exposure instrumental variables, and the susceptibility and severity of sepsis in the UK Biobank were used as outcomes. The inverse-variance weighted (IVW), MR-Egger, and weighted median methods were used to evaluate the causal relationship between exposure and outcomes. Heterogeneity was assessed using IVW and MR-Egger’s and Cochran’s Q tests, and pleiotropy was tested using the MR-Egger intercept and MR-PRESSO.

Results: Using the IVW method, a one-standard-deviation increase in genetically determined carnitine levels was found to be associated with increased susceptibility to sepsis in populations under 75 years of age (odds ratio [OR]: 2.696; 95% confidence interval [CI]: 1.127-6.452; P = 0.026) and increased severity of sepsis (OR: 22.31; 95% CI: 1.769-281.282; P = 0.016). Sensitivity analysis did not reveal heterogeneity or horizontal pleiotropy; therefore, the results indicated robustness.

Conclusion: Genetic susceptibility to increased carnitine levels in the blood may increase the susceptibility and severity of sepsis. Therefore, interventions at an early stage in patients with high carnitine levels may reduce the risk of developing sepsis.

Keywords

Carnitine / Causality / Genome-wide association study (GWAS) / Mendelian randomization / Sepsis

Conflict of interest statement

Yuguo Chen is the Editor-in-Chief of Emergency and Critical Care Medicine. The article was subject to the journal’s standard procedures, with peer review handled independently of the Editor-in-Chief and their research groups. The authors declare no conflict of interest.

Author contributions

Pang J and Chen Y designed the study; Zhang X analyzed and interpreted the data; Zhang X, Zhang Q, and Shen Q wrote the manuscript. Wang X revised the manuscript. Pang J and Chen Y provided material support for this study. Final approval of the manuscript was obtained from all the authors.

Funding

This study was supported by the State Key Program of the National Natural Science Foundation of China (82030059), National Natural Science Foundation of China (82172127, 81772036, 82072144, 81671952, 81873950, and 81873953), National Key R&D Program of China (2020YFC1512700, 2020YFC1512705, 2020YFC15127 03, and 2020YFC0846600), National S&T Fundamental Resources Investigation Project (2018FY100600, 2018FY100602), Taishan Pandeng Scholar Program of Shandong Province (tspd20181220), Taishan Young Scholar Program of Shandong Province (tsqn201610 65, tsqn201812129), Youth Top-Talent Project of National Ten Thousand Talents Plan, Qilu Young Scholar Program, and the Fun-damental Research Funds of Shandong University (2018JC011).

Ethical approval of studies and informed consent

This study was based on data from a public database. All studies included in the analyses received ethics approval from a relevant Institutional Review Board and followed the principles of the Declaration of Helsinki as revised in 2013, and all participants had provided informed consent. The study was exempt from the approval of the institutional review board as it used de-identified, publicly available data.

Acknowledgments

We express our gratitude to the researchers for their generously sharing the GWAS data used in this study.

References

[1] GBD 2019 Antimicrobial Resistance Collaborators. AGlobal mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2022; 400(10369):2221-2248. doi:10.1016/s0140-6736(22)02185-7

[2] Brealey D, Brand M, Hargreaves I, et al. Association between mitochondrial dysfunction and severity and outcome of septic shock. Lancet. 2002; 360(9328):219-223. doi:10.1016/s0140-6736(02)09459-x

[3] Lira Chavez FM, Gartzke LP, van Beuningen FE, et al. Restoring the infected powerhouse: mitochondrial quality control in sepsis. Redox Biol. 2023; 68:102968. doi:10.1016/j.redox.2023.102968

[4] Gómez H. Reprogramming metabolism to enhance kidney tolerance during sepsis: the role of fatty acid oxidation, aerobic glycolysis, and epithelial de-differentiation. Nephron. 2023; 147(1):31-34. doi:10.1159/000527392

[5] Cetinkaya A, Erden A, Avci D, et al. Is hypertriglyceridemia a prognostic factor in sepsis? Ther Clin Risk Manag. 2014; 10:147-150. doi:10.2147/tcrm.S57791

[6] Xiao M, Deng H, Mao W, et al. U-shaped association between serum triglyceride levels and mortality among septic patients: an analysis based on the MIMIC-IV database. PloS One. 2023; 18(11):e0294779. doi:10.1371/journal.pone.0294779

[7] Rebouche CJ. Kinetics, pharmacokinetics, and regulation of L-carnitine and acetyl-L-carnitine metabolism. Ann N Y Acad Sci. 2004; 1033:30-41. doi:10.1196/annals.1320.003

[8] Longo N, Amat di san Filippo C, Pasquali M. Disorders of carnitine transport and the carnitine cycle. Am J Med Genet C Semin Med Genet. 2006; 142C(2):77-85. doi:10.1002/ajmg.c.30087

[9] Houten SM, Violante S, Ventura FV, Wanders RJ. The biochemistry and physiology of mitochondrial fatty acid beta-oxidation and its genetic disorders. Annu Rev Physiol. 2016; 78:23-44. doi:10.1146/annurev-physiol-021115-105045

[10] Drosatos K, Schulze PC. Cardiac lipotoxicity: molecular pathways and therapeutic implications. Curr Heart Fail Rep. 2013; 10(2):109-121. doi:10.1007/s11897-013-0133-0

[11] Ferreira GC, McKenna MC. L-carnitine and acetyl-L-carnitine roles and neuroprotection in developing brain. Neurochem Res. 2017; 42(6):1661-1675. doi:10.1007/s11064-017-2288-7

[12] Maldonado C, Vázquez M, Fagiolino P. Potential therapeutic role of carnitine and acetylcarnitine in neurological disorders. Curr Pharm Des. 2020; 26(12):1277-1285. doi:10.2174/1381612826666200212114038

[13] Thooft A, Conotte R, Colet JM, Zouaoui Boudjeltia K, Biston P, Piagnerelli M. Serum metabolomic profiles in critically ill patients with shock on admission to the intensive care unit. Metabolites. 2023; 13(4):523. doi:10.3390/metabo13040523

[14] Pandey S, Siddiqui MA, Azim A, Sinha N. Metabolic fingerprint of patients showing responsiveness to treatment of septic shock in intensive care unit. MAGMA. 2023; 36(4):659-669. doi:10.1007/s10334-022-01049-9

[15] Mickiewicz B, Tam P, Jenne CN, et al. Integration of metabolic and inflammatory mediator profiles as a potential prognostic approach for septic shock in the intensive care unit. Crit Care. 2015; 19(1):11. doi:10.1186/s13054-014-0729-0

[16] Langley RJ, Tsalik EL, van Velkinburgh JC, et al. An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med. 2013; 5(195):195ra95. doi:10.1126/scitranslmed.3005893

[17] Famularo G, De Simone C, Trinchieri V, Mosca L. Carnitines and its congeners: a metabolic pathway to the regulation of immune response and inflammation. Ann N Y Acad Sci. 2004; 1033:132-138. doi:10.1196/annals.1320.012

[18] Vandebergh M, Dubois B, Goris A. Effects of vitamin D and body mass index on disease risk and relapse hazard in multiple sclerosis: a Mendelian randomization study. Neurol Neuroimmunol Neuroinflamm. 2022; 9(3):e1165. doi:10.1212/nxi.0000000000001165

[19] Sheehan NA, Meng S, Didelez V. Mendelian randomisation: a tool for assessing causality in observational epidemiology. Methods Mol Biol. 2011; 713:153-166. doi:10.1007/978-1-60327-416-6_12

[20] Chen X, Hong X, Gao W, et al. Causal relationship between physical activity, leisure sedentary behaviors and COVID-19 risk: a Mendelian randomization study. J Transl Med. 2022; 20(1):216. doi:10.1186/s12967-022-03407-6

[21] Pairo-Castineira E, Clohisey S, Klaric L, et al. Genetic mechanisms of critical illness in COVID-19. Nature. 2021; 591(7848):92-98. doi:10.1038/s41586-020-03065-y

[22] Ponsford MJ, Gkatzionis A, Walker VM, et al. Cardiometabolic traits, sepsis, and severe COVID-19: a Mendelian randomization investigation. Circulation. 2020; 142(18):1791-1793. doi:10.1161/circulationaha.120.050753

[23] Baranova A, Cao H, Zhang F. Causal effect of COVID-19 on Alzheimer's disease: a Mendelian randomization study. J Med Virol. 2023; 95(1):e28107. doi:10.1002/jmv.28107

[24] Walley KR, Boyd JH, Kong HJ, Russell JA. Low low-density lipoprotein levels are associated with, but do not causally contribute to, increased mortality in sepsis. Crit Care Med. 2019; 47(3):463-466. doi:10.1097/ccm.0000000000003551

[25] Butler-Laporte G, Harroud A, Forgetta V, Richards JB. Elevated body mass index is associated with an increased risk of infectious disease admissions and mortality: a Mendelian randomization study. Clin Microbiol Infect. 2021; 27(5):710-716. doi:10.1016/j.cmi.2020.06.014

[26] Hamilton FW, Thomas M, Arnold D, et al. Therapeutic potential of IL6R blockade for the treatment of sepsis and sepsis-related death: a Mendelian randomisation study. PLoS Med. 2023; 20(1):e1004174. doi:10.1371/journal.pmed.1004174

[27] Shin SY, Fauman EB, Petersen AK, et al. An atlas of genetic influences on human blood metabolites. Nat Genet. 2014; 46(6):543-550. doi:10.1038/ng.2982

[28] Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601. doi:10.1136/bmj.k601

[29] Roberts GHL, Partha R, Rhead B, et al. Expanded COVID-19 phenotype definitions reveal distinct patterns of genetic association and protective effects. Nat Genet. 2022; 54(4):374-381. doi:10.1038/s41588-022-01042-x

[30] Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013; 37(7):658-665. doi:10.1002/gepi.21758

[31] Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-egger method. Eur J Epidemiol. 2017; 32(5):377-389. doi:10.1007/s10654-017-0255-x

[32] Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018; 50(5):693-698. doi:10.1038/s41588-018-0099-7

[33] Greco MF, Minelli C, Sheehan NA, Thompson JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015; 34(21):2926-2940. doi:10.1002/sim.6522

[34] Hemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017; 13(11):e1007081. doi:10.1371/journal.pgen.1007081

[35] Hemani G, Zheng J, Elsworth B, et al. The MR-base platform supports systematic causal inference across the human phenome. Elife. 2018; 7:e34408. doi:10.7554/eLife.34408

[36] Burgess S, Scott RA, Timpson NJ, Davey Smith G, Thompson SG. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015; 30(7):543-552. doi:10.1007/s10654-015-0011-z

[37] Wang Y, Ye J, Ganapathy V, Longo N. Mutations in the organic cation/carnitine transporter OCTN2 in primary carnitine deficiency. Proc Natl Acad Sci U S A. 1999; 96(5):2356-2360. doi:10.1073/pnas.96.5.2356

[38] Pauly DF, Pepine CJ. The role of carnitine in myocardial dysfunction. Am J Kidney Dis. 2003; 41(4Suppl 4): S35-S43. doi:10.1016/s0272-6386(03)00115-x

[39] Cave MC, Hurt RT, Frazier TH, et al. Obesity, inflammation, and the potential application of pharmaconutrition. Nutr Clin Pract. 2008; 23(1):16-34. doi:10.1177/011542650802300116

[40] Chen Z, Lu D, Qi B, et al. Quantitative profiling of serum carnitines facilitates the etiology diagnosis and prognosis prediction in heart failure. Molecules. 2023; 28(14):5345. doi:10.3390/molecules28145345

[41] Schmerler D, Neugebauer S, Ludewig K, Bremer-Streck S, Brunkhorst FM, Kiehntopf M. Targeted metabolomics for discrimination of systemic inflammatory disorders in critically ill patients. J Lipid Res. 2012; 53(7):1369-1375. doi:10.1194/jlr.P023309

[42] Pochini L, Galluccio M, Scalise M, Console L, Pappacoda G, Indiveri C. OCTN1: a widely studied but still enigmatic organic cation transporter linked to human pathology and drug interactions. Int J Mol Sci. 2022; 23(2):914. doi:10.3390/ijms23020914

[43] Scalise M, Console L, Galluccio M, Pochini L, Indiveri C. Chemical targeting of membrane transporters: insights into structure/function relationships. ACS Omega. 2020; 5(5):20692080-20692080. doi:10.1021/acsomega.9b04078

[44] Pochini L, Pappacoda G, Galluccio M, Pastore F, Scalise M, Indiveri C. Effect of cholesterol on the organic cation transporter OCTN1 (SLC22A4). Int J Mol Sci. 2020; 21(3):1091. doi:10.3390/ijms21031091

[45] Koepsell H. Organic cation transporters in health and disease. Pharmacol Rev. 2020; 72(1):253-319. doi:10.1124/pr.118.015578

[46] Pochini L, Scalise M, Galluccio M, Pani G, Siminovitch KA, Indiveri C. The human OCTN1 (SLC22A4) reconstituted in liposomes catalyzes acetylcholine transport which is defective in the mutant L503F associated to the Crohn's disease. Biochim Biophys Acta. 2012; 1818(3):559-565. doi:10.1016/j.bbamem.2011.12.014

[47] Stanley CA. New genetic defects in mitochondrial fatty acid oxidation and carnitine deficiency. Adv Pediatr. 1987; 34:59-88.

[48] Shiraki M, Shimizu M, Moriwaki H, Okita K, Koike K. Carnitine dynamics and their effects on hyperammonemia in cirrhotic Japanese patients. Hepatol Res. 2017; 47(4):321-327. doi:10.1111/hepr.12750

[49] Hanai T, Shiraki M, Imai K, Suetugu A, Takai K, Shimizu M. Usefulness of carnitine supplementation for the complications of liver cirrhosis. Nutrients. 2020; 12(7):1915. doi:10.3390/nu12071915

[50] Michels EHA, Butler JM, Reijnders TDY, et al. Association between age and the host response in critically ill patients with sepsis. Crit Care. 2022; 26(1):385. doi:10.1186/s13054-022-04266-9

[51] Cederblad G. Plasma carnitine and body composition. Clin Chim Acta. 1976; 67(2):207-212. doi:10.1016/0009-8981(76)90261-8