Skip to main content

Remote ischaemic preconditioning influences the levels of acylcarnitines in vascular surgery: a randomised clinical trial

Abstract

Background

Vascular surgery patients have reduced tissues` blood supply, which may lead to mitochondrial dysfunction and accumulation of acylcarnitines (ACs). It has been suggested that remote ischaemic preconditioning (RIPC) has its organ protective effect via promoting mitochondrial function. The aim of this study was to evaluate the effect of RIPC on the profile of ACs in the vascular surgery patients.

Methods

This is a randomised, sham-controlled, double-blinded, single-centre study. Patients undergoing open surgical repair of abdominal aortic aneurysm, surgical lower limb revascularisation surgery or carotid endarterectomy were recruited non-consecutively. The RIPC protocol consisting of 4 cycles of 5 min of ischaemia, followed by 5 min of reperfusion, was applied. A blood pressure cuff was used for RIPC or a sham procedure. Blood was collected preoperatively and approximately 24 h postoperatively. The profile of ACs was analysed using the AbsoluteIDQp180 kit (Biocrates Life Sciences AG, Innsbruck, Austria).

Results

Ninety-eight patients were recruited and randomised into the study groups and 45 patients from the RIPC group and 47 patients from the sham group were included in final analysis. There was a statistically significant difference between the groups regarding the changes in C3-OH (p = 0.023)—there was a decrease (− 0.007 µmol/L, ± 0.020 µmol/L, p = 0.0233) in the RIPC group and increase (0.002 µmol/L, ± 0.015 µmol/L, p = 0.481) in the sham group. Additionally, a decrease from baseline to 24 h after surgery (p < 0.05) was detected both in the sham and the RIPC group in the levels of following ACs: C2, C8, C10, C10:1, C12, C12:1, C14:1, C14:2, C16, C16:1, C18, C18:1, C18:2. In the sham group, there was an increase (p < 0.05) in the levels of C0 (carnitine) and a decrease in the level of C18:1-OH. In the RIPC group, a decrease (p < 0.05) was noted in the levels of C3-OH, C3-DC (C4-OH), C6:1, C9, C10:2.

Conclusions

It can be concluded that RIPC may have an effect on the levels of ACs and might therefore have protective effects on mitochondria in the vascular surgery patients. Further larger studies conducted on homogenous populations are needed to make more definite conclusions about the effect of RIPC on the metabolism of ACs.

Trial registration

ClinicalTrials.gov database, NCT02689414. Registered 24 February 2016—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02689414.

Background

Remote ischaemic preconditioning (RIPC) is an experimental procedure in which short episodes of ischaemia are induced in order to offer organ protection to distant tissues. We along other investigators have demonstrated that RIPC has protective effects to heart, kidneys, brain and other organs in the case of ischaemia–reperfusion injury [1,2,3,4,5]. The exact mechanisms of RIPC are not known, but during the last decade multiple pathways and biochemical markers involved in achieving the effect of RIPC have been discovered. It has been found that cardioprotection by RIPC occurs along with improved mitochondrial function in animal studies [6, 7]. As ischaemia–reperfusion injury is known to impair mitochondrial function, the effect of RIPC might be beneficial in reducing the extent of injury. Ischaemia–reperfusion injury is inevitable in vascular surgery. Also, surgery induces acute stress response, which in turn promotes catabolic pathways including fatty-acid catabolism in beta-oxidation hereby increasing the load on mitochondria even more. Mitochondria have a principal position in energy metabolism and intensification of the beta-oxidation of fatty acids in mitochondria leads to elevated ATP production due to integrated action of the Krebs cycle and the respiratory chain. In the case of mitochondrial dysfunction, fatty acid β-oxidation is diminished, resulting in accumulation of acylcarnitines (ACs) [8, 9]. ACs are esters of l-carnitine and fatty acids and due to existence of different fatty acids [10], a large set of ACs can be produced that are generally divided into short, medium and long chain ACs (denoted as SCACs, MCACs and LCACs). For transport of fatty acid into mitochondria for beta-oxidation, the coenzyme A group is attached and afterwards displaced by carnitine forming an acylcarnitine, which is able to enter the mitochondrial matrix where it can be broken down by carnitine palmitoyl transferase II to release activated fatty acid to enter beta-oxidation [11]. It is crucial to produce LCACs as mitochondrial inner membrane is impenetrable for long chain fatty acids. Because of this, the increase of LCACs is most commonly associated with metabolic disorders such as mitochondrial dysfunction and genetic enzyme deficiencies [11]. However, as more knowledge has been gained about the role of SCACs and MCACs, it is necessary to simultaneously investigate changes of SCACs, MCACs and LCACs.

Considering all this, shifts in the ACs profile might occur in response to RIPC in patients undergoing vascular surgery. To our knowledge, no studies have been published about the effect of RIPC on the whole profile (C2–C18) of ACs.

This is a substudy within our large clinical trial conducted for evaluating the effect of RIPC on arterial stiffness and end-organ damage [1, 2, 12]. Among our secondary aims was to investigate changes in the levels of ACs. We hypothesised that RIPC may prevent the increase of the levels of ACs, ensuing from metabolic shifts in patients undergoing vascular surgery and the aim of the current study was to test this hypothesis.

Methods

Study groups and eligibility

This randomised double-blinded sham-controlled clinical trial was conducted at the Department of Vascular Surgery, Clinic of Surgery, at Tartu University Hospital.

Patients undergoing open surgical repair of infra-renal abdominal aortic aneurysm (AAA) or surgical lower limb revascularisation surgery (for claudication or critical limb ischaemia; common femoral artery endarterectomy, aorto(bi)femoral or femoropopliteal or femorotibial or iliofemoral bypass surgery) or carotid endarterectomy (for symptomatic or asymptomatic carotid stenosis) during the period from January 1, 2016 to February 8, 2018 were recruited non-consecutively.

Signed informed consent was obtained from each patient.

The research protocol of our study was approved by the Research Ethics Committee of the University of Tartu, and was registered in the ClinicalTrials.gov database (NCT02689414).

The following exclusion criteria were applied: age under 18 years, pregnancy, known malignancy in the past 5 years, permanent atrial fibrillation or flutter, symptomatic upper limb atherosclerosis, need for oxygen therapy at home, estimated preoperative glomerular filtration rate (eGFR) < 30 mL/min/1.73 m2, myocardial infarction in the past month, previous history of upper limb vein thrombosis or vascular surgery in the axillary region, and inability to follow the study regimen.

Intervention

The RIPC protocol consisted of four 5-min episodes of ischaemia with a 5-min period of reperfusion between the episodes, which has been one of the most often used protocols in earlier studies. Ischaemia was achieved by placing a blood pressure cuff on an arm and raising cuff pressure to 200 mmHg. In case the patient’s blood pressure exceeded 180 mmHg, the cuff pressure was raised to a value that was 20 mmHg higher than systolic blood pressure. For sham group patients, cuff pressure was kept at level of venous pressure (10–20 mmHg). Intervention began along with preparation for anaesthesia in the operating theatre. Any other aspects of surgery, including anaesthesia and medication use, were not affected. The principal investigator was in charge of patient recruitment, assignment to intervention and data storage.

Blinding

The patient, surgeon, anaesthesiologist and everyone else in the surgical team were blinded to study intervention. The scale of the manometer was kept covered. The statistician was blinded to the meaning of the group affiliation.

Outcomes

Blood samples for analysis of ACs were collected in the morning of surgery and approximately 24 h after surgery. The last blood collection was set as close as possible to 24 h after surgery on condition that the patient had fasted for at least 3 h. Blood samples were centrifuged, serum was separated and stored in the refrigerator at − 80 °C.

The levels of ACs were analysed using the AbsoluteIDQp180 kit (Biocrates Life Sciences AG, Innsbruck, Austria). The analytical procedure was performed according to the manufacturer’s standard protocol in the laboratory of the Department of Biochemistry, University of Tartu. In brief, for targeted analysis of metabolites internal standard was pipetted onto a 96-well extraction plate and 10 µL serum was added to each well. Drainage was achieved with nitrogen and derivatisation was performed with phenylisothiocyanate. The measurements were accomplished with QTRAP 4500 (ABSciex, USA) coupled to an Agilent 1260 series HPLC (USA), using the C18 column and flow injection analysis. The vendor’s software with internal standards’ intensities was used to calculate the concentrations of ACs along with other metabolites, which are not discussed in this paper.

Blood samples for analysis of high sensitivity troponin T (hs-TnT) and N-terminal pro-brain natriuretic peptide (NT-proBNP) which were used to calculate correlations, were collected along with the samples for analysis of ACs preoperatively and approximately 24 h after surgery. The levels of cardiac biomarkers were analysed at the United Laboratories of Tartu University Hospital.

Sandwich electrochemiluminescence immunoassays (ECLIA), specifically the Elecsys troponin T high-sensitive assay as STAT version (Roche Diagnostics) and Elecsys proBNP II (Roche Diagnostics) were used according to the manufacturer’s protocol for analysis of hs-TnT and NT-proBNP.

All patients were asked about their previous and current health issues and medications; an electronic health database was also used for complete anamnesis.

Statistical analysis

Two groups were compared using Student’s t test or the Wilcoxon rank-sum or Chi-squared test as appropriate. Student’s t test was used in baseline characteristics comparison where normal distribution was present. Wilcoxon rank-sum test was used in baseline comparison where normal distribution was not present. Because of the issue of multiple comparison, Benjamini–Hochberg procedure was used to control false discovery rate. For assessing correlations between changes in the levels of AC and cardiac biomarkers, Spearman’s correlation coefficient was employed.

P values under 0.05 were considered significant. Statistical analysis was performed by a qualified statistician from the University of Tartu.

As the study’s primary outcomes were parameters of arterial stiffness, calculation of sample size was based on their values [12]. For both groups, calculated sample size was 44.

Results

Ninety-eight patients were recruited and randomised into the study groups and 45 patients from the RIPC group and 47 patients from the sham group were included in final analysis.

Detailed patient flow is depicted in Fig. 1. The median time from the end of intervention to the beginning of surgery did not differ significantly (p = 0.057) between the RIPC (36 min, IQR 21–46 min) and the sham group (25 min, IQR 15–38 min). There were no significant differences in the baseline values of ACs (Additional file 1). The baseline characteristics (including medications, comorbidities, preoperative risk of surgery) of the two groups were similar (Table 1). No adverse events due to RIPC were described and no patient found the RIPC or the sham procedure unbearable.

Fig. 1
figure1

Patients’ flow chart

Table 1 Baseline characteristics

Changes in the levels of ACs in the RIPC and in the sham group (Table 2)

Table 2 Changes in the levels of acylcarnitine esters from baseline to 24 h postoperatively

There was a statistically significant difference between the groups regarding the changes in C3-OH (p = 0.023)—there was a significant decrease (− 0.007 µmol/L, ± 0.020 µmol/L, p = 0.0233) in the RIPC group and insignificant increase (0.002 µmol/L, ± 0.015 µmol/L, p = 0.481) in the sham group.

A statistically significant decrease (p < 0.05) was detected both in the sham and the RIPC group in the levels of following ACs: C2, C8, C10, C10:1, C12, C12:1, C14:1, C14:2, C16, C16:1, C18, C18:1, C18:2. In the sham group, there was a statistically significant increase (p < 0.05) in the levels of C0 (carnitine) and a statistically significant decrease in the level of C18:1-OH. In the RIPC group, a statistically significant decrease (p < 0.05) was noted in the levels of C3-OH, C3-DC (C4-OH), C6:1, C9, C10:2.

Correlations between change in hs-TnT and changes in the levels of ACs (Table 3)

Table 3 Substantial correlations between cardiac biomarkers (i.e. high sensitivity troponin T and NT-proBNP) and acylcarnitines

In the RIPC group, there were statistically significant positive correlations between change of hs-TnT and change of C4 (cor = 0.38, p = 0.01), C10 (cor = 0.38, p = 0.010), C10:1 (cor = 0.38, p = 0.010), C12:1 (cor = 0.31, p = 0.037), C18:1 (cor = 0.32, p = 0.030) and C18-OH (cor = 0.35, p = 0.019). In the sham group, there was statistically significant negative correlation between change of hs-TnT and change of C5-OH (cor = − 0.34, p = 0.021). No other significant correlations were observed between changes in the levels of hs-TnT and ACs in the sham group.

Correlations between change in NT-proBNP and changes in the levels of ACs (Table 3)

In the RIPC group a statistically significant positive correlation occurred between change of NT-proBNP and change of C16:2 (cor = 0.34, p = 0.021). In the sham group, a statistically significant positive correlation occurred between change of NT-proBNP and change of C18 (cor = 0.31, p = 0.031) and statistically significant negative correlation between change of NT-proBNP and change of C16:1 (cor = − 0.35, p = 0.016).

Discussion

There have been no studies evaluating the effect of RIPC on the level of carnitine (C0) and on the profile of all acylcarnitines (C2–C18). In this study we describe the positive effect of RIPC in lowering the levels of several ACs in patients undergoing vascular surgery. We noted a statistically significant difference in changes in the level of C3-OH between the RIPC and sham groups. In addition, there was a statistically significant increase in the levels of C0 in the sham group, no significant increase occurred in the levels of any ACs but a statistically significant decrease occurred in the levels of C3, C3-OH, C3-DC (C4-OH), C4, C5, C6:1, C9, C10:2 in the RIPC group. All these findings indicate the RIPC-directed effect on the ACs profile in plasma.

Based on previous studies, the decrease in the levels of ACs can be associated with preserved mitochondrial function [9] whereas their increase has been linked to increased mortality in chronic heart failure patients [8] and worse prognosis in patients with IgA nephropathy [13]. Several carnitine esters and members of the ACs are elevated in patients with peripheral artery disease (PAD) [14]. Nevertheless, the impact of ACs in clinical practice is unknown as relevant studies are lacking. Considering the results of the studies published about ACs, knowledge of the ACs profile may facilitate assessment of the patients’ general metabolic milieu, mitochondrial functioning and prognosis.

ACs have a different origin in plasma. The main precursors of SCACs are branched chain amino acids (BCAAs) but some SCASs are also produced by catabolism of glucose and some triglycerides. MCACs and LCACS are only derived from fatty acid metabolism whereas carnitine is required for transporting long-chain fatty acids into mitochondria [15]. SCASs in plasma has been found to be released from the liver [16], MCACs, from the skeletal muscles and liver [17] and LCACs, from the heart [15]. Taken together, the exact origin of plasma ACs is not clear, yet based on the assessment of whole ACs spectrum, conclusions can be drawn about the whole-body acylcarnitine metabolism. We observed an increase of some SCACs levels in the sham group whereas no any increase of ACs occurred in the RIPC group. It should be noted that the hepatoprotective effect of RIPC has been reported previously [4, 18].

Evidently, the stress caused by surgery enhances the catabolism of BCCA in the liver in order to produce additional metabolic energy and this is accompanied by an increase of plasma SCACs. RIPC has been found to intensify hepatic oxygenation and hepatic microcirculation via activation of eNOS [19], as well as to increase expression of protector proteins (e.g. heme oxygenase 1) [20], which preserves mitochondrial functionality. Hence, produced SCACs can be spent more efficiently in the case of RIPC and, based on our findings we could suppose that RIPC might have a protective effect on the liver. Surgery increases the demand for metabolic energy may also cause elevated level of ketone bodies leading to production of C3-OH. In RIPC, the elimination of this SCAC is more effective compared to the sham group, which results in a statistically significant difference between these groups.

As a response to any surgery, the human organism intensifies the production of metabolic energy, which is accompanied by additional spending of long chain fatty acids for energy-rich substrates through LCACs. This can explain for the decline in LCASs both in the sham and the RIPC group.

The cardioprotective effect of RIPC has been studied on humans since 2006 [21], however, results are contradictory. Although a previously published systematic review on patients undergoing non-cardiac vascular surgery reports no effect of RIPC in reducing myocardial injury [22], its cardioprotective effect has been described in more homogenous and more powerful studies with other populations. Cardioprotection by RIPC has been associated with the improved function of mitochondria [23,24,25]. However, two of these studies failed to demonstrate an effect of RIPC on cardioprotection and hence also correlation between cardioprotection and salvage of mitochondrial function [23, 24].

Previously, we have published a study on the same cohort, where we demonstrated positive effects of RIPC in reducing the levels of hsTnT and NT-proBNP [2]. In the present study, we describe positive correlations between decrease of these cardiac biomarkers and decrease of several ACs in the RIPC group. In the sham group, no positive correlations were noted between increase of hsTnT and increase of ACs. On the contrary, there was negative correlation between increase of hsTnT and increase of C5-OH. Also there was a negative correlation between increase of NT-proBNP and C16:2 and positive correlation between increase of NT-proBNP and C18. The strength of correlations may have been weakened by inter-individual variations in the AC profiles coming from inter-individual differences in metabolism. Also, if our study had been larger, more definite conclusions about these correlations could be made. Although the changes of the above mentioned ACs between the groups were not significant, these differences between the sham and the RIPC group and the previously described cardioprotective effects of RIPC in the same cohort [2] suggest that the cardioprotective effects could be described basing on shifts in the levels of ACs.

However, further studies are needed to clarify these assumptions.

There are several limitations to our study. Firstly, the study population was heterogeneous as was also presumably their metabolic status. Although, there were no differences between study groups regarding comorbidities, health status, most common antihypertensive medications, treatment with statins and the baseline values of ACs, there might be a variation in response of ACs metabolism. It has been found that the levels of ACs differ among patients with different stages of PAD those without PAD [14]. As in our study there were patients with different locations and stages of atherosclerotic lesions, their metabolic status was evidently different, which may have influenced the results. Also we recruited both diabetic and non-diabetic patients in our groups and diabetes has been found to affect the levels of ACs [26] and have a deleterious effect on RIPC [27, 28]. Moreover, the patients underwent different types of surgery and the extent of tissue damage was different. The patients undergoing open surgical repair of AAA probably experienced larger tissue damage and were not chronically preconditioned against ischaemia like might have been PAD patients who were undergoing lower limb revascularisation surgery. Thus the type of surgery may have had a great impact on the metabolism of ACs and the effect of RIPC may have been overwhelmed. In addition, in 42% of the patients in the RIPC group propofol-induced anaesthesia was used and propofol has been found to reduce the effect of RIPC [29]. Also, the size of the study group was relatively small and the true effect of RIPC might have been missed as there were multiple differences between the groups, which did not quite reach statistical significance.

Conclusions

It can be concluded that RIPC may have an effect on the levels of ACs and might therefore have protective effects on mitochondria in the vascular surgery patients. Further larger studies conducted on homogenous populations are needed to make more definite conclusions about the effect of RIPC on the metabolism of ACs.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AAA:

Abdominal aortic aneurysm

ACs:

Acylcarnitines

LCACs:

Long chain acylcarnitines

MSCASs:

Medium chain acylcarnitines

PAD:

Peripheral artery disease

RIPC:

Remote ischaemic preconditioning

SCASc:

Short chain acylcarnitines

References

  1. 1.

    Kasepalu T, Kuusik K, Lepner U, Starkopf J, Zilmer M, Eha J, et al. Remote ischaemic preconditioning reduces kidney injury biomarkers in patients undergoing open surgical lower limb revascularisation: a randomised trial. Oxid Med Cell Longev. 2020. https://doi.org/10.1155/2020/7098505.

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Kepler T, Kuusik K, Lepner U, Starkopf J, Zilmer M, Eha J, et al. Remote ischaemic preconditioning attenuates cardiac biomarkers during vascular surgery: a randomised clinical trial. Eur J Vasc Endovasc Surg Off J Eur Soc Vasc Surg. 2020;59:301–8. https://doi.org/10.1016/j.ejvs.2019.09.502.

    Article  Google Scholar 

  3. 3.

    Zhang Y, Ma L, Ren C, Liu K, Tian X, Wu D, et al. Immediate remote ischemic postconditioning reduces cerebral damage in ischemic stroke mice by enhancing leptomeningeal collateral circulation. J Cell Physiol. 2019;234:12637–45. https://doi.org/10.1002/jcp.27858.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Wu G, Chen M, Wang X, Kong E, Yu W, Sun Y, et al. Effect of remote ischemic preconditioning on hepatic ischemia–reperfusion injury in patients undergoing liver resection: a randomized controlled trial. Minerva Anestesiol. 2019. https://doi.org/10.23736/S0375-9393.19.13838-2.

    Article  PubMed  Google Scholar 

  5. 5.

    Pryds K, Bøttcher M, Sloth AD, Munk K, Rahbek Schmidt M, Bøtker HE. Influence of preinfarction angina and coronary collateral blood flow on the efficacy of remote ischaemic conditioning in patients with ST segment elevation myocardial infarction: post hoc subgroup analysis of a randomised controlled trial. BMJ Open. 2016. https://doi.org/10.1136/bmjopen-2016-013314.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Gedik N, Maciel L, Schulte C, Skyschally A, Heusch G, Kleinbongard P. Cardiomyocyte mitochondria as targets of humoral factors released by remote ischemic preconditioning. Arch Med Sci AMS. 2017;13:448–58. https://doi.org/10.5114/aoms.2016.61789.

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Paez DT, Garces M, Calabró V, Bin EP, D’Annunzio V, Del Mauro J, et al. Adenosine A1 receptors and mitochondria: targets of remote ischemic preconditioning. Am J Physiol Heart Circ Physiol. 2019;316:H743–50. https://doi.org/10.1152/ajpheart.00071.2018.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Reuter SE, Evans AM. Carnitine and acylcarnitines: pharmacokinetic, pharmacological and clinical aspects. Clin Pharmacokinet. 2012;51:553–72. https://doi.org/10.1007/bf03261931.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Bjørndal B, Alterås EK, Lindquist C, Svardal A, Skorve J, Berge RK. Associations between fatty acid oxidation, hepatic mitochondrial function, and plasma acylcarnitine levels in mice. Nutr Metab. 2018. https://doi.org/10.1186/s12986-018-0241-7.

    Article  Google Scholar 

  10. 10.

    Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vázquez-Fresno R, et al. HMDB 4.0: the human metabolome database for 2018. Nucl Acids Res. 2018;46:D608–17. https://doi.org/10.1093/nar/gkx1089.

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    McGill MR, Li F, Sharpe MR, Williams CD, Curry SC, Ma X, et al. Circulating acylcarnitines as biomarkers of mitochondrial dysfunction after acetaminophen overdose in mice and humans. Arch Toxicol. 2014;88:391–401. https://doi.org/10.1007/s00204-013-1118-1.

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Kepler T, Kuusik K, Lepner U, Starkopf J, Zilmer M, Eha J, et al. The effect of remote ischaemic preconditioning on arterial stiffness in patients undergoing vascular surgery: a randomised clinical trial. Eur J Vasc Endovasc Surg. 2019;57:868–75. https://doi.org/10.1016/j.ejvs.2018.12.002.

    Article  PubMed  Google Scholar 

  13. 13.

    Xia F-Y, Zhu L, Xu C, Wu Q-Q, Chen W-J, Zeng R, et al. Plasma acylcarnitines could predict prognosis and evaluate treatment of IgA nephropathy. Nutr Metab. 2019;16:2. https://doi.org/10.1186/s12986-018-0328-1.

    Article  Google Scholar 

  14. 14.

    Ismaeel A, Franco ME, Lavado R, Papoutsi E, Casale GP, Fuglestad M, et al. Altered metabolomic profile in patients with peripheral artery disease. J Clin Med. 2019. https://doi.org/10.3390/jcm8091463.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Makrecka-Kuka M, Sevostjanovs E, Vilks K, Volska K, Antone U, Kuka J, et al. Plasma acylcarnitine concentrations reflect the acylcarnitine profile in cardiac tissues. Sci Rep. 2017;7:1–11. https://doi.org/10.1038/s41598-017-17797-x.

    CAS  Article  Google Scholar 

  16. 16.

    Schooneman MG, Ten Have GAM, van Vlies N, Houten SM, Deutz NEP, Soeters MR. Transorgan fluxes in a porcine model reveal a central role for liver in acylcarnitine metabolism. Am J Physiol Endocrinol Metab. 2015;309:E256–64. https://doi.org/10.1152/ajpendo.00503.2014.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Xu G, Hansen JS, Zhao XJ, Chen S, Hoene M, Wang XL, et al. Liver and muscle contribute differently to the plasma acylcarnitine pool during fasting and exercise in humans. J Clin Endocrinol Metab. 2016;101:5044–52. https://doi.org/10.1210/jc.2016-1859.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Kanoria S, Robertson FP, Mehta NN, Fusai G, Sharma D, Davidson BR. Effect of remote ischaemic preconditioning on liver injury in patients undergoing major hepatectomy for colorectal liver metastasis: a pilot randomised controlled feasibility trial. World J Surg. 2017;41:1322–30. https://doi.org/10.1007/s00268-016-3823-4.

    Article  PubMed  Google Scholar 

  19. 19.

    Abu-Amara M, Yang SY, Quaglia A, Rowley P, Fuller B, Seifalian A, et al. Role of endothelial nitric oxide synthase in remote ischemic preconditioning of the mouse liver. Liver Transpl Off Publ Am Assoc Study Liver Dis Int Liver Transpl Soc. 2011;17:610–9. https://doi.org/10.1002/lt.22272.

    Article  Google Scholar 

  20. 20.

    Cornide-Petronio ME, Jiménez-Castro MB, Gracia-Sancho J, Peralta C. Ischemic preconditioning directly or remotely applied on the liver to reduce ischemia–reperfusion injury in resections and transplantation. Liv Dis Surg. 2019. https://doi.org/10.5772/intechopen.86148.

    Article  Google Scholar 

  21. 21.

    Cheung MMH, Kharbanda RK, Konstantinov IE, Shimizu M, Frndova H, Li J, et al. Randomized controlled trial of the effects of remote ischemic preconditioning on children undergoing cardiac surgery: first clinical application in humans. J Am Coll Cardiol. 2006;47:2277–82. https://doi.org/10.1016/j.jacc.2006.01.066.

    Article  PubMed  Google Scholar 

  22. 22.

    Stather PW, Wych J, Boyle JR. A systematic review and meta-analysis of remote ischemic preconditioning for vascular surgery. J Vasc Surg. 2019;70:1353-1363 e3. https://doi.org/10.1016/j.jvs.2019.03.025.

    Article  PubMed  Google Scholar 

  23. 23.

    Ferko M, Kancirová I, Jašová M, Čarnická S, Muráriková M, Waczulíková I, et al. Remote ischemic preconditioning of the heart: protective responses in functional and biophysical properties of cardiac mitochondria. Physiol Res. 2014;63(Suppl 4):S469-478.

    CAS  PubMed  Google Scholar 

  24. 24.

    Slagsvold KH, Moreira JBN, Rognmo Ø, Høydal M, Bye A, Wisløff U, et al. Remote ischemic preconditioning preserves mitochondrial function and activates pro-survival protein kinase Akt in the left ventricle during cardiac surgery: a randomized trial. Int J Cardiol. 2014;177:409–17. https://doi.org/10.1016/j.ijcard.2014.09.206.

    Article  PubMed  Google Scholar 

  25. 25.

    Petra K, Nilguen G, Mücella K, Leanda S, Ulrich F, Afsaneh Z, et al. Mitochondrial and contractile function of human right atrial tissue in response to remote ischemic conditioning. J Am Heart Assoc. 2018;7:e009540. https://doi.org/10.1161/JAHA.118.009540.

    Article  Google Scholar 

  26. 26.

    Schooneman MG, Vaz FM, Houten SM, Soeters MR. Acylcarnitines: reflecting or inflicting insulin resistance? Diabetes. 2013;62:1–8. https://doi.org/10.2337/db12-0466.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Moretti C, Cerrato E, Cavallero E, Lin S, Rossi ML, Picchi A, et al. The EUROpean and Chinese cardiac and renal Remote Ischemic Preconditioning Study (EURO-CRIPS CardioGroup I): a randomized controlled trial. Int J Cardiol. 2018;257:1–6. https://doi.org/10.1016/j.ijcard.2017.12.033.

    Article  PubMed  Google Scholar 

  28. 28.

    Wider J, Undyala VV, Whittaker P, Przyklenk K. Abstract 19195: remote ischemic preconditioning fails to reduce infarct size in type-2 diabetes: role of defective humoral communication. Circulation. 2017;136:A19195–A19195. https://doi.org/10.1161/circ.136.suppl_1.19195.

    Article  Google Scholar 

  29. 29.

    Behmenburg F, van Caster P, Bunte S, Brandenburger T, Heinen A, Hollmann MW, et al. Impact of anesthetic regimen on remote ischemic preconditioning in the rat heart in vivo. Anesth Analg. 2018;126:1377–80. https://doi.org/10.1213/ANE.0000000000002563.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors are indebted to Ms. E. Jaigma for the linguistic revision of the text.

Funding

This study was supported by grants from the Estonian Research Council (PUT No. 1169, PUT PRG685, IUT No. 20-42, IUT No. 2-7, PRG435, PRG1054), and by the European Union through the European Regional Development Fund (Project No. 2014-2020.4.01.15-0012).

Author information

Affiliations

Authors

Contributions

TK, KK, UL, JS, MZ, JE and JK contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript. TK was the main contributor in writing the manuscript. JK conceived the original idea. MV performed the statistical analysis. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Teele Kasepalu.

Ethics declarations

Ethics approval and consent to participate

Signed informed consent was obtained from each patient. The research protocol of our study was approved by the Research Ethics Committee of the University of Tartu (Protocol’s No. 252/M-24).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations

Supplementary information

Additional file 1: Table S1

. Baseline values of acylcarnitines. Table S2. Non-substantial correlations between cardiac biomarkers (i.e. high sensitivity troponin T and NT-proBNP) and acylcarnitines.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kasepalu, T., Kuusik, K., Lepner, U. et al. Remote ischaemic preconditioning influences the levels of acylcarnitines in vascular surgery: a randomised clinical trial. Nutr Metab (Lond) 17, 76 (2020). https://doi.org/10.1186/s12986-020-00495-3

Download citation

Keywords

  • Acylcarnitines
  • Ischaemic preconditioning
  • Mitochondria
  • Vascular surgery